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How AI In Healthcare Will Headgear Hospital Infrastructure In 2024?

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Do you know that 10 out of 1000 people around the globe have some or other kind of genetic disorder? (as per reports of WHO). Most of these disorders are easily trackable and can be put on early diagnosis and treatment by preventable health care. That’s where AI in healthcare will leap multifold to bridge the gap. In this article, many other areas where AI in medical infrastructure is destined to shape years to come.

- Updated: 28th Dec 2023, 17:14 IST
  • 1
    Traditional Healthcare System v/s Evolved Healthcare in Modern Time
  • 2
    Working Model of AI in Healthcare
  • 3
    How is AI bringing a big-time change?
    • Diagnosis
    • Analysis and Decision Making
    • Research and Development
    • Tackling Emergency
    • Achieving Health Equity
  • 4
    Challenges posed by AI in healthcare intervention
  • 5
    Summary: AI In Healthcare
    • AI tackling treatment gap.

Artificial Intelligence is spreading its wing in almost all aspects of human life. However artificial it may sound through its name, technology is changing lives like never before. This assists in providing potential solutions to all the major problems for humanity. Our scope of discussion in this article surrounds how AI in healthcare will make an impacting change in coming days.

It is beyond any question to suspect the importance of AI in almost every domain. However, the way AI has been spearheading the 21st-century revolution in the health sector is commendable. The vast amount of data pertaining to every patient often makes no value if they cannot be analysed for early detection and diagnosis.

Artificial intelligence in healthcare thereby helps in filling this gap. Modern science has evolved beyond measures in the past few years. There has been greater acceptability that the scope of AI in healthcare cannot be limited.

Dr Rachit Singhania from the Department of Psychiatry at Himalayan Hospital in Dehradun spoke to the Cashify Techbyte at length and provided us with some valuable input with regards to AI presenting the verticals of opportunities and challenges in tackling mental health.

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Traditional Healthcare System v/s Evolved Healthcare in Modern Time

The era bestowed to humanity after COVID laid its wing in 2019 has seen how AI has been unimaginably great in managing healthcare systems around the world. Even though there were minute developments hither and tither, the pandemic time opened the floodgate of the utility in healthcare infrastructure.

Traditionally, the healthcare system involved many manual tasks and paper-based work that could not be tracked holistically. Even though the filing system made collating all the reports in one place easier, the relevant information was often lost.

According to Dr Singhania, “ChatGPT and related AI platforms hold enormous potential in many fields, including mental health. They carry vast utilisation possibilities and are coming in a big way. It is not hard to predict that they will make a massive difference in the mental healthcare delivery system. There is a huge treatment gap in mental health care in developing, lower, and lower-middle-income countries.”

With the introduction of AI, the reports can be summarised and tracked easily. You do not have to carry hundreds of prescriptions, diagnosis reports, etc. Administrative work like patient registration or tracking, revenue processing, and maintaining health records can all be easily tackled. Besides, it helps in facilitating research and development based on disease mapping and modelling, such as during COVID.

Also Read: The Future Of Artificial Intelligence: Applications & Implications

Working Model of AI in Healthcare

working model

Pre-processing: This stage ensures that the electronic health record (EHR) collects the data in a raw form without any manipulation. This is generally done in bulk.

Deep Learning: This raw data set is then processed using deep learning technology to complete the task by understanding and working on an extensive data set to produce desirable results.

The neural networks are trained in such a way that different layers produce higher representation when compared to the last layer.

In the picture represented above, AI uses predictive analytics to produce accurate information based on dates presented by EHR.

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How is AI bringing a big-time change?

One cannot emphasise the importance of AI. Especially after how the central management of databases helped track and keep records of COVID-affected patients. In India alone, the presence of AI-based record-keeping made tracking COVID patients and providing them with necessary amenities easier.

A special app in the form of Aarogya Setu and CoWIN made this possible. Besides, tracking vaccination status to spread awareness among people and keep a regular update on the statistics of people vaccinated throughout the country.

Summarising the positives presented by Dr. Singhania about AI in the field of mental health care alone, “The ability of ChatGPT and other AI-based chatbots to generate human-quality responses can provide companionship, support, and therapy for people who have problems with accessibility and affordability in terms of time, distance, and finances. The ease, convenience, and simulation of talking to another human being make it a superior app for providing psychotherapies.”

However, we look into the bigger picture to understand different fields where AI in healthcare is bringing a big-time change.

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Diagnosis

Artificial Intelligence has helped in diagnosing diseases through accurate prediction and analysis. This helps make drug prescriptions easier and identifies people at higher risk of disease. Besides, through the application of Natural language processing (NLP), understanding medical history, and symptoms become easy to decipher, helping to screen patients with rare ailments and genetic medical conditions.

Analysis and Decision Making

AI in healthcare analysis

As data is pulled from a large data set, analysis becomes simpler and even more accurate. The AI-based platform can help in gene sequencing and analyse patients that can be at greater risk in the coming times. This makes drug prescription and treatment more accessible.

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Research and Development

R&D

Having access to data from patients and regions around the globe gives an optimism to conduct research and development in the field of medicine. After all, it’s pretty convenient to map disease and likewise conduct research as and when required. Transcribing medical reports, and predicting events based on the available data are all possible through the use of research and development.

Tackling Emergency

ai in healthcare emergency

Imagine going through multiple tests during a suspicion of breast cancer. One has to run the hospital, secure reports of the test conducted, and consult a doctor again to understand if there is any prevalence of cancer. However, AI’s presence in healthcare is becoming more accessible. The patient’s report is compared to thousands of reports in the database. This is further checked for calcification and soft tissue lesions.

Thereafter, it provides a score depending on which patient is prescribed a test. This is really helpful in tackling other problems like lung infection, tuberculosis, and other conditions, such as getting medical help from professionals at the tip of their fingers.

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Achieving Health Equity

equity

With the large spread of AI-based medical healthcare, achieving health equity is not a distant dream anymore. In fact, many experts speculate that this technology will make medical care available for anyone and everyone at a very cost-effective price. Healthcare planning to allocate and invest in resources becomes simpler.

Challenges posed by AI in healthcare intervention

One cannot simply negate the pluses put forward by the intervention of AI in the healthcare system. However, there are a few challenges too that cannot be minimised until proper governance is ensured:

  • Loss of critical data may pose serious data handling issues. Information like patent detail and medical profile can be misused by businesses as well as external agencies that have not been authorised to use the data legally.
  • Lack of data can even lead to inaccurate reporting, and hence result from that might lead to problems in prescribing proper medications.  “AI-based chatbots are programmed and trained with vast knowledge about psychiatric conditions and respond with empathy. Still, they cannot diagnose specific mental health conditions and provide treatment details reliably and accurately.”, says Dr Rachit Singhania from Himalayan Hospital, Dehradun.

    Adding to this, he believes that AI platforms are trainable and trained using web-based information and utilise the reinforcement learning technique with human feedback. If not prepared with proper responses and from authentic sites, they can provide wrong information regarding the condition and inappropriate advice, which may be potentially harmful to persons with mental problems. This brings us to our next challenge, enumerated in the coming pointer.
  • Lack of trust due to people still believing in the traditional methods of diagnosis as compared to machine-led results.

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Summary: AI In Healthcare

According to the decision-making search engine Plat AI, the AI has 72.52 per cent accuracy in diagnosing a disease when compared to the average doctor, who can be 71.4 per cent accurate in such a condition. The evolution of virtual health assistants can help reduce a layer where a specialised person caters to understanding the symptom of the patient.

Instead, everything is reported in a summarised form to a doctor. Proper medication can be given even at the wee hours of the day and in the most remote locations. AI has enormous scope for advancement in the time to come, but the way it has perpetrated human life by making life-changing evolution in medical infrastructure has to be given due credit.

AI tackling treatment gap.

According to National Mental Health Survey, the treatment gap reported for any mental disorder in India is as high as 83 per cent. As Dr Singhania puts it, “A huge deficit of mental health professionals far below the specified norms. The inequitable resource distribution make the gap more prominent. AI and digital interfaces are emerging as viable alternatives for reducing this gap. This would make psychiatric diagnosis and treatment accessible and affordable.”

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Highlights of the Story

  • AI in healthcare is one sector where technology has positively impacted millions of lives.
  • With AI’s growth, the application domain has also increased multi-fold.
  • Let’s throw light on how AI in the healthcare infrastructure is going to shape the years to come.

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