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Tech Opportunity in India

As technologies can bring

Need to Ease Challenges

In India, AI can potentially bound some other technologies, but to be used at any scale, digitalisation is a prerequisite. In many Indian healthcare centres, medical records are still paper registered, and radiology still uses films. Considering other countries, this scenario is changing rapidly.

Technology can be transformative in healthcare services delivery, improving the quality of life, even where there is a density of doctors is one per thousands of people. Since AI, data analytics, machine learning among others have been transforming care services, India is one of the countries in the world with huge scope to improve medical treatment. With AI, data analytics and all the technology there, treatments can perhaps be done better in India as we go forward. Former Niti Aayog Vice-Chairman Arvind Panagariya said, “India’s health sector is still very much evolving and very informal as it is still largely dominated by the private sector and government’s role largely had been into setting up medical colleges.”As technologies can bring healthcare services closer to the community, India can be benefited from an integrated health information system (HIS) across all states. With this system, both doctors and patients will have the access to manage all aspects of healthcare planning, delivery, and monitoring, such as disease observation, patient medical records, planning for human resources, continuing medical education, facility registration, and telemedicine initiatives. Over the last decade, the country has seen rapid diffusion in the internet and smartphones and now it is meeting the requirements for efficient delivery of digital care solutions. The interest for innovation from governments made technology is at an all-time high at the central policy level, along with at the local level. At present, every state is seeking to surpass each other at the adoption of new technology that can assist and support overcome old problems. Arvind says “The biggest problem that India had was that in the rural areas and even in tier 2-3 cities, the qualified doctors just don’t go and much of the provision is done by people who have just kind of learned the job or somebody who have worked as an assistant with a doctor.” The convergence of technological solutions with cloud computing, data analytics, telecommunications, and wireless technologies will also enhance the accessibility and manage shortages of skilled doctors or physicians more efficiently in the healthcare chúng tôi India, AI can potentially bound some other technologies, but to be used at any scale, digitalisation is a prerequisite. In many Indian healthcare centres, medical records are still paper registered, and radiology still uses films. Considering other countries, this scenario is changing rapidly. Another challenge that needs to overcome is the cost of delivering medical services, which has been increasing steadily. When technological innovation is better incorporated with healthcare delivery, it can enable scale and minimise costs, stimulating adoption. This adoption will also be driven by the automation of critical processes in administration, finance, billing, patient records, and pharmacies.

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Applications Of Ai And Big Data Analytics In M

Have you heard about the idea of monitoring health with the help of mobile devices?

It is related to the term m-Health that makes use of m-Health apps along with AI and Big Data in healthcare. Owing to the surge in the usage of smartphones and other devices, people have started interacting with doctors and hospitals differently. You will realize there is an app for every task right from managing doctor’s appointments to maintaining records.

At this juncture, where every business is fighting hard to appeal to the interests and goals of the customers AI and big data are redefining the healthcare industry. In this blog, we will take a look at the applications of AI and big data and how it has revolutionized the entire healthcare system.

Let’s begin:

AI in Healthcare

AI in healthcare relates to the usage of machine learning algorithms and software to mimic human cognition that aids in analysis, presentation, and understanding of complex data.

Right from detecting links between genetic codes, putting surgical robots to use, or maximizing hospital efficiency, AI is a powerful tool to streamline the healthcare industry. Let’s see what AI has to offer to healthcare:

1. AI Supports Decision Making

Healthcare developers and professionals must consider a crucial piece of information for app development and diagnosis. They go through various complicated unstructured information in medical records. A single mistake can have huge implications.

AI in healthcare makes it convenient for everyone to narrow down the big chunks of information into relevant pieces of information.

It can store and organize these large chunks of information and provide a knowledge database that can, later on, facilitate inspection and analysis to draw meaningful conclusions. This way, it helps clinical decision support, where doctors can rely on it for detecting risk factors.

One such example of AI is IBM’s Watson that predicts heart failure with the help of AI.

2. Chatbots to Prioritize and Enhance Primary Care

People tend to book appointments even at the slightest of medical issues, which often causes chaos and confusion. Later on, there are usually discovered to be issues that could be taken care of by self-treatment. Here AI can be of great use to enable smooth flow and automation that facilitates primary care. It will help doctors to focus more on critical cases.

The best example is medical chatbots that can save you from medical trips to doctors that could be easily avoided. Chatbots when incorporated with smart algorithms can provide patients with instant answers to patient queries and concerns.

Also read: Top 3 Lessons I Learned from Growing a $100K+ Business

3. Robotic Surgeries

A combination of AI in healthcare and collaborative robots has helped achieve desired speed and depth in making delicate incisions. These surgeries have been given the name of robotic surgeries that eliminates the issue of fatigue and helps in lengthy and critical medical procedures.

With the help of AI, one can develop new surgical methods from past operations that will help gain more preciseness. This accuracy and precision will surely reduce accidental movements during the surgeries.

The best example of robotic surgeries is Vicarious Surgical, which combines virtual reality with AI-enabled robots. The purpose of developing such robots is to help surgeons perform minimally invasive operations.

Another great example of AI in robotic surgery is the Heartlander. It is a miniature mobile robot aimed to facilitate heart therapy. The robot is developed by the robotics department at Carnegie Mellon University.

4. Virtual nursing assistants

Virtual nursing assistants are another example of AI in healthcare that can help in providing excellent healthcare services by way of performing a range of tasks. These tasks include addressing patient queries, directing them to the best and effective care unit, monitoring high-risk patients, assisting with admissions and discharge, and surveying patients in real-time. The best part is that you can avail the services of these virtual nurses 24/7 and get instant solutions to your problems.

When you explore the market, you would realize many AI-powered applications of virtual nursing assistants are in use. They help facilitate regular interactions between patients and care providers that save the patients from unnecessary hospital visits. Care Angel is the world’s first virtual nurse assistant that facilitates wellness checks through voice and AI.

5. Accurate Diagnosis of Diseases

AI in healthcare can surpass human efforts and help in the detection, prediction, and diagnosis of diseases quickly and accurately. Have a look at the specialty-level diagnosis, here AI algorithms have proven to be cost-effective in the detection of diseases like diabetic retinopathy.

PathAI is a machine learning technology that helps pathologists in determining the issues with more accuracy. It aims to reduce errors in cancer diagnosis and develop methods for individual medical treatment.

How Machine Learning Is Transforming Healthcare In India

The integration of machine learning in the healthcare industry of India is set to transform conventional methods

Healthcare has become one of the biggest sectors in India’s economy. According to a report from

Solving the problem: too much raw data, too few real insights

Healthcare settings are flooded with unprecedented volumes of complex data from clinicians’ notes, medical devices, labs, and more. Remote patient wearables are increasingly adding to the onslaught. Electronic health records are helping digitize the information, but their job is not to ease the administrative workload on the front end or provide at-a-glance decision support. All the data coming in is only as valuable as the insights that can be quickly gleaned from it and appropriately actioned to improve healthcare delivery. Machine learning can make that possible, especially for digitized data sets with clear patterns. Machine learning not only collects but also unifies, data from disparate sources. It can perform the complex calculations required for doctors, nurses, and other members of the healthcare team to make quick sense of raw physiological, behavioral, and imaging information.

Automation of manual tasks

Machine learning reduces the workload of physicians, radiologists, pathologists, and other providers by employing algorithms to garner insights. Automated workflows designed around how healthcare teams work in the real world are often used in tandem for easy information sharing and collaboration. Typical applications include:

Imaging analysis leveraging widely available data sets

Precise patient monitoring in the ICU or OR

Real-time remote patient monitoring through wearables that track heart rate, activity level, and more

Streamlining tedious administrative tasks like clinical documentation

Powerful predictive capabilities

Precise predictive analysis of what a given patient will likely need next has historically been stopped by two barriers: the burden of collecting data and the difficulty of calculation. With machine learning, data collection speed and calculation complexity no longer depend on what humans can do by hand. Using these powerful algorithms, one can imagine treatment decisions tailored to each patient’s specific situation and better outcomes as a result.

Digital transformation: what to expect next

India is poised for an exciting digital transformation in healthcare. The penetration of machine learning and other innovative technologies, including automation and other AI techniques like natural language processing, is surging—with 5G coming soon. A vibrant ecosystem of startup and established health-tech companies is now in-country, with a rising population to fill new roles. Healthcare providers have gained a greater awareness of tech-enabled ways to do more with less manual effort. The government has stepped up with increased spending on evolving healthcare delivery, and the general public is in support.

Government’s mission is to transform the healthcare infrastructure

Since 2023 due to the Covid-19 pandemic, there has been a huge focus by the government on investing in India’s healthcare infrastructure. This has also enabled technology firms to dive into the healthcare segment and innovate to contribute to the improvement of healthcare facilities in the country. Under the Digital India Initiative, the government has recently announced the launch of the Ayushman Bharat Health Mission which aims at creating India’s digital health ecosystem. The initiative focuses on creating digital health records for the citizens and their families to access and share digitally. Under this mission, the citizens will receive a randomly generated 14-digit number used for the purposes of uniquely identifying persons, authenticating them, and threading their health records only with their informed consent across multiple systems and stakeholders. Moreover, inclusion is one of the key principles of ABDM. The digital health ecosystem created by ABDM supports continuity of care across primary, secondary, and tertiary healthcare in a seamless manner. It aids the availability of health care services, particularly in remote and rural areas through various technology interventions like telemedicine etc. Digital health start-ups in India provide a vast backdrop for solutions with the government’s push to strengthen the digital healthcare infrastructure. The start-up landscape within the Indian healthcare ecosystem goes well beyond a specific disease, therapeutic area, geography, type of product, and service or business model. In a country where access to affordable healthcare is still a looming issue, the public stands to gain immensely from the development of the Digital Health industry. The ABDM is a one-of-a-kind strategy to unify the healthcare system in India and promote innovation in the industry. With the public interest in the minds of both the Government as well as the innovators, it remains to be seen how Digital Health will be perceived in law. While there is a long way to go, the use of AI and ML has gained a strong foothold in India over the past year and we foresee a promising future for the industry.

Author:

Healthcare has become one of the biggest sectors in India’s economy. According to a report from NITI Ayog , the sector has grown at a compound annual growth rate (CAGR) of 22% since 2023. Millions of jobs have been created, with millions more to come. How can a country short on trained clinical resources with vast inequities in care distribution grow at this pace? Machine learning is one way to help close the gaps.Healthcare settings are flooded with unprecedented volumes of complex data from clinicians’ notes, medical devices, labs, and more. Remote patient wearables are increasingly adding to the onslaught. Electronic health records are helping digitize the information, but their job is not to ease the administrative workload on the front end or provide at-a-glance decision support. All the data coming in is only as valuable as the insights that can be quickly gleaned from it and appropriately actioned to improve healthcare delivery. Machine learning can make that possible, especially for digitized data sets with clear patterns. Machine learning not only collects but also unifies, data from disparate sources. It can perform the complex calculations required for doctors, nurses, and other members of the healthcare team to make quick sense of raw physiological, behavioral, and imaging information.Machine learning reduces the workload of physicians, radiologists, pathologists, and other providers by employing algorithms to garner insights. Automated workflows designed around how healthcare teams work in the real world are often used in tandem for easy information sharing and collaboration. Typical applications include:Precise predictive analysis of what a given patient will likely need next has historically been stopped by two barriers: the burden of collecting data and the difficulty of calculation. With machine learning, data collection speed and calculation complexity no longer depend on what humans can do by hand. Using these powerful algorithms, one can imagine treatment decisions tailored to each patient’s specific situation and better outcomes as a result.India is poised for an exciting digital transformation in healthcare. The penetration of machine learning and other innovative technologies, including automation and other AI techniques like natural language processing, is surging—with 5G coming soon. A vibrant ecosystem of startup and established health-tech companies is now in-country, with a rising population to fill new roles. Healthcare providers have gained a greater awareness of tech-enabled ways to do more with less manual effort. The government has stepped up with increased spending on evolving healthcare delivery, and the general public is in support.Since 2023 due to the Covid-19 pandemic, there has been a huge focus by the government on investing in India’s healthcare infrastructure. This has also enabled technology firms to dive into the healthcare segment and innovate to contribute to the improvement of healthcare facilities in the country. Under the Digital India Initiative, the government has recently announced the launch of the Ayushman Bharat Health Mission which aims at creating India’s digital health ecosystem. The initiative focuses on creating digital health records for the citizens and their families to access and share digitally. Under this mission, the citizens will receive a randomly generated 14-digit number used for the purposes of uniquely identifying persons, authenticating them, and threading their health records only with their informed consent across multiple systems and stakeholders. Moreover, inclusion is one of the key principles of ABDM. The digital health ecosystem created by ABDM supports continuity of care across primary, secondary, and tertiary healthcare in a seamless manner. It aids the availability of health care services, particularly in remote and rural areas through various technology interventions like telemedicine etc. Digital health start-ups in India provide a vast backdrop for solutions with the government’s push to strengthen the digital healthcare infrastructure. The start-up landscape within the Indian healthcare ecosystem goes well beyond a specific disease, therapeutic area, geography, type of product, and service or business model. In a country where access to affordable healthcare is still a looming issue, the public stands to gain immensely from the development of the Digital Health industry. The ABDM is a one-of-a-kind strategy to unify the healthcare system in India and promote innovation in the industry. With the public interest in the minds of both the Government as well as the innovators, it remains to be seen how Digital Health will be perceived in law. While there is a long way to go, the use of AI and ML has gained a strong foothold in India over the past year and we foresee a promising future for the industry.Punit Soni, Founder & CEO, Suki

Best 5 Conversational Ai Uses In Healthcare

The pandemic has caused a shortage in the global healthcare workforce, including nurses and doctors. Several reforms have been suggested by countries around the globe to address this shortage. These reforms include reducing the barriers international medical graduates face while practicing, as well as easing the licensing process for physicians. The technology industry is not the only one that is changing. Conversational Artificial Intelligence, (AI), is ready to save the healthcare industry from this grave crisis.

Chatbot for Patient Engagement

The post-treatment phase can be kept engaged by patients using conversational AI in healthcare. Now we are familiar with the ways bots can help patients schedule appointments and diagnose problems. The post-treatment phase is as important if not more.

Scheduling An Appointment

Website/app visitors can access a chatbot via a messaging interface. Chatbots can make appointments according to doctor availability. Chatbots can also be programmed to communicate with CRM systems such as Salesforce or Microsoft Dynamics to track patient visits and follow-up appointments. This information can then be saved for future reference.

How Brand Management Can Be Enhanced In The Age Of Ai

Artificial Intelligence (AI) has actively taken the world by storm. More and more businesses are now planning to leverage AI to develop brand management strategies as a fundamental part of their vision and mission

Meanwhile, AI is slowly but steadily becoming more prevalent in customers’ day-to-day lives. It makes everyday tasks and small chores easier and is quickly becoming more readily available in lots of shapes and sizes to suit customers’ needs.

Google and Microsoft are among the popular global brands that have already regulated their business operations to focus on Artificial Intelligence research. Other industry leaders like IBM, Amazon, Facebook, Apple, and Alibaba are not far behind from this objective.

According to a market research firm IDC, global spending on AI systems is said to reach $57.6 billion in 2023.

While AI offers undeniable benefits such as cost savings for the business, the bigger goal for marketers is to enhance brand management by making it more predictive and personalized. So, specifically, how can AI help marketers to achieve this? Without any further ado, we’ll discuss various methods to improve brand management using AI.

AI guards online reputation

We know that opinions spread like wildfire online. Word of mouth is powerful enough to enhance brand awareness or wreck it altogether. Managing online reputation in this tightly connected world can be quite challenging for organizations.

A recent report by Bright Local found that marketers are spending, on average, 17% of their workweek on online reputation management. That’s almost one full day of work per week.

Of course, social media monitoring is essential for business success, but that doesn’t mean it should dominate your work time. The use of AI tools simplifies this task.

Artificial intelligence, using natural language processing (NLP) models, means computers can understand and decipher what your audience is saying.

AI offers a better way to ease the time commitment of managing your reputation online by:

Automating the monitoring process.

Responding to and asking for reviews at the right time.

Enabling brand managers and product managers to research on a large-scale basis.

Monitoring social media, websites, and other online forums.

Download our Business Resource – Social media marketing strategy guide

Access the Social media marketing strategy guide

AI connects you with the right audience

Before the introduction of AI, companies were broadly categorizing customers to make bulk decisions about customer experience. AI has entirely changed how companies monitor their CX.

AI records and analyzes every action made by a user, such as:

The items they browsed

The products they added to the cart and then removed

The items remaining in the cart

Consider the example of Premier Inn, the largest hotel chain in the UK. The company was able to reach out to the target audience who were looking for a place to stay by leveraging the signals of their search queries.

By connecting to the right users with the right message at the right time, they saw an increase in their hotel bookings by 40%!

AI improves customer experience

Forming an emotional connection with a brand plays a crucial role in enhancing the customer experience. Apple is the perfect example of a company that leverages emotions to build an everlasting bond with its consumers. Instead of sending out press releases about a product launch, it creates events to nurture a sense of mystery and allows consumers to be a part of it.

Marketers can achieve this intense relationship by utilizing the power of AI. These tools collect and analyze tons of data, giving access to accurate information to drive marketing strategies, and contributing directly to improved customer experience.

According to Forbes, the future of customer experience is artificial intelligence. In fact, it is projected that 95% of customer interactions will be managed by AI technology by 2025.

Companies are also focusing on using AI to deliver personalized recommendations. This is another crucial factor necessary to achieve a better customer experience. For example, we have already seen chatbots helping brands in this area by offering a personalized experience.

Intelligent chatbots deliver a comprehensive communication solution when it comes to answering FAQs, providing sales suggestions, or guiding a customer where to go next. With this approach, one need not have to call in or wait on hold for a customer representative. The automated live chat will answer all the common inquiries.

AI secures customer data

Digitization has brought tremendous benefits to organizations, but it has also made them more exposed to cyber threats. Over the years, we have seen online attacks dramatically increasing.

In the wake of these outbreaks, eight out of ten online customers in the U.S are becoming increasingly concerned about data security and privacy as per 2023 CIGI-Ipsos Global Survey. This clearly indicates that most online users feel like they’ve lost control over how their information is being collected and used online.

The data protection laws such as GDPR and CCPA are introduced to secure the customer’s personal data and instill their trust in the favorite brands. These laws come with a massive penalty for the companies that are involved in leaking sensitive customer data.

According to the European Data Protection Board, supervisory authorities in the 31 countries reported 206,326 cases of GDPR infringement from May 25, 2023, to mid-March 2023.

With more number of companies embracing the Cloud and digital technologies, it’s now more critical than ever to protect the crucial data. Fortunately, business leaders and experts believe that artificial intelligence (AI) can improve data security to a certain extent.

AI-driven security tools can do this either by themselves using automation and detection or by offering security teams and Security Operation Centers (SOCs) with enhanced capabilities.

Examples of AI-powered data security solutions include:

User and Entity Behavior Analytics (UEBA) – This tool learns specific patterns of legitimate access usage and uses it to determine sophisticated attacks like insider threats.

Security Information and Event Management (SIEM) – This security tool helps the security team deal with various events across the entire organizational environment. With the information delivered by SIEM, one can quickly deal with data security threats in real-time.

Security, Orchestration, Automation, and Response (SOAR) – This cybersecurity solution alerts on threats. It can detect risks and deal with some of them automatically.

Apart from this, some firms utilize AI systems like facial, voice, and sound recognition to register customer’s biometrics, which can then be used to securely access facilities in the future.

Bottom line

The above-specified ways help companies in enhancing brand management using AI tools. Through these techniques, companies can earn higher revenue in terms of increased sales and conversions. Enhanced brand management is crucial to surviving in the competitive business environment, so brand managers should seek funds to invest in AI at the earliest and reap the benefit.

How Emotional Ai Is Changing The Mental Healthcare Profile?

AI as Medical Assistants

Emotion AI can free up doctors to work more with their patients by analyzing patient records and generating reports based on the data, handling administrative tasks, and even assisting with diagnosis or intervention. This can help patients to have better and customized treatment as per their needs, medical conditions and preference without any necessity of divulging the same to the examiner. The software can help patients with mental health issues by using voice analysis. It can also address and regulate their emotions better even when they are under a severely stressful or traumatic state. One such application is Affectiva. It uses a webcam to measure a person’s heart rate without wearing a sensor by tracking color changes in the person’s face, which pulses each time the heartbeats.

AI as Emotional Support

A ‘nurse bot’ not only reminds older patients on long-term medical programs to take their medication but also converses with them every day to monitor their overall wellbeing. Along with this, they make sure to interact with people with recent accident history or depression to elevate their mood levels. Moreover, it gives a definitive picture of how a patient responds to new medications.

AI as Chatbot

In a society where mental illness is stigmatized and considered as a taboo, seeking medical help is challenging for people. AI helps in closing this gap by chatbots where physical accessibility is not possible. Researchers have discovered that people are comfortable in talking to avatars than a therapist. Not only that, but these chatbots also allow people to talk about their issues any time of the day or night, anywhere around the world. These chatbots are fed with mock transcripts from counselors, physicians that allow them to deal with a wide array of issues. Some of the chatbots offer either free or low monthly subscription fees. This can help tremendously to people with lower incomes. Mood tracking apps like Woebot, which is created by a team of Stanford psychologists and AI experts, uses brief daily chat conversations, mood tracking, curated videos, and word games to help people manage mental health.

Using AI to Identify At-Risk Person

Social Media Networking Sites like Facebook use AI to monitor posts to detect signs of a user’s depression. This could spot the disorder three months before those people were formally diagnosed by health care providers. An fMRI scan used AI to analyze brain scans and spot likely cases to have Bipolar Disorder and major depressive disorder with 92.4% accuracy.

Humans have often debated how futuristic AI’s emotional range be. Will it understand the basic conscience and existential questions man finds bothersome and worrying himself about? Or will it have normal selective feelings of happiness, sadness, envy, anger, fear? These doubts come in a spectrum relatable to movies like Her and WALL-E. While in former, the protagonist falls in love with an intelligent computer operating system personified through a female voice called Samantha who does not reciprocate the same, leading to heartbreak, the later ends up restarting life on Earth after facing a challenging journey guided by its emotions and wit to comprehend things around him. But things now provide a bit of clarity on the picture of Emotional AI. Also called as facial coding, Emotional recognition technology. The field dates back to 1990 when psychology professors John D Mayer and Peter Salovey coined the term emotional intelligence. Fast forward to the current age, Emotional AI has countless possibilities and scope to assist humans in everyday life. From businesses, it can capture peoples’ emotional reactions in real-time. It can decode facial expressions, analyze voice patterns, greet cheerfully, scan e-mails for the tone of language, and measure neurological immersion levels. It helps autistic kids identify other people’s emotions. Using computer vision technology AI can monitor the driver’s emotional state and level of drowsiness. In the workplace environment, it can help to analyze the stress and anxiety levels of employees who have very demanding jobs. Of all the fields, emotional AI has interesting potentials in the medical sector, in ways of revolutionizing it.Emotion AI can free up doctors to work more with their patients by analyzing patient records and generating reports based on the data, handling administrative tasks, and even assisting with diagnosis or intervention. This can help patients to have better and customized treatment as per their needs, medical conditions and preference without any necessity of divulging the same to the examiner. The software can help patients with mental health issues by using voice analysis. It can also address and regulate their emotions better even when they are under a severely stressful or traumatic state. One such application is Affectiva. It uses a webcam to measure a person’s heart rate without wearing a sensor by tracking color changes in the person’s face, which pulses each time the heartbeats.A ‘nurse bot’ not only reminds older patients on long-term medical programs to take their medication but also converses with them every day to monitor their overall wellbeing. Along with this, they make sure to interact with people with recent accident history or depression to elevate their mood levels. Moreover, it gives a definitive picture of how a patient responds to new chúng tôi a society where mental illness is stigmatized and considered as a taboo, seeking medical help is challenging for people. AI helps in closing this gap by chatbots where physical accessibility is not possible. Researchers have discovered that people are comfortable in talking to avatars than a therapist. Not only that, but these chatbots also allow people to talk about their issues any time of the day or night, anywhere around the world. These chatbots are fed with mock transcripts from counselors, physicians that allow them to deal with a wide array of issues. Some of the chatbots offer either free or low monthly subscription fees. This can help tremendously to people with lower incomes. Mood tracking apps like Woebot, which is created by a team of Stanford psychologists and AI experts, uses brief daily chat conversations, mood tracking, curated videos, and word games to help people manage mental health.Social Media Networking Sites like Facebook use AI to monitor posts to detect signs of a user’s depression. This could spot the disorder three months before those people were formally diagnosed by health care providers. An fMRI scan used AI to analyze brain scans and spot likely cases to have Bipolar Disorder and major depressive disorder with 92.4% accuracy. Adopting measures to deal with the increasing number of mental health problems is the need of the hour. When a person finds themselves under excruciating strain and pressure or is a victim of communal negligence existing in a society where having depression or any mental disorder is met by raised eye-brows of contempt and ignorance, it can harm them to unknowable ends. According to a paper published, one in seven Indians were affected by mental disorders of varying severity in 2023. If the inclusion of emotional AI can provide them with much needed help and lighten the country’s medical expenses, it is beneficial to invest in this technology as soon as possible.

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