AI revolutionising medical diagnoses

The Indian healthcare space, particularly after the Covid pandemic, is fast evolving with the adoption of technology like artificial intelligence (AI) and machine learning. It is bringing in a paradigm shift in healthcare practices besides revolutionising the field of medicine by improving accuracy of diagnoses and providing new methods of treatment. Medical diagnosis with AI brings in time-bound precision for speedy decisions to treatment access and is bringing in major transformation in the way a primary physician will extend treatment protocols. By analysing large amounts of medical data and identifying patterns that may not be apparent to the human eye, AI can help doctors by identifying diseases when they are most treatable.

One of the most promising applications of AI in medicine is in the field of diagnosis. AI algorithms can be trained to recognize signs of cancer in medical images such as mammograms or X-rays. This can help to improve the accuracy of diagnoses and reduce the number of false negatives. AI can also be used to analyse patient records and identify patterns that may indicate a particular disease. Further AI algorithms can be used to create personalized treatment plans for patients based on their medical history and current condition. They can also be deployed in clinical decision support systems where optimum treatment strategies can be developed by analysing vast amounts of patient-specific data such as clinical features, laboratory, and radiological investigations.

A notable application of AI is in drug development. Here AI algorithms can be used to analyse vast amounts of data from clinical trials and identify new drug targets. It can control robots performing complex surgeries, such as brain surgery, with greater precision than human surgeons.

AI will fundamentally transform medicine in its diagnostics and patient care as technology engages the doctor in two ways. One is the supportive care extended to patient and the other is to reduce the doctor’s human cognitive load. From a patient’s perspective, AI gives attention to genomics and epigenetics, which bring in robustness to the structured make-up of the human body. It indicates the time dependent wear and tear durability. Therefore, genomic + Big Data provides patterns of the body condition with AI. These are new emerging areas are seen as dominant mechanisms for understanding the functioning of the body system.

Technology has made healthcare more accurate by providing medical professionals with new ways to diagnose and treat patients. Diagnostic tools like MRIs and CT scans have helped doctors diagnose illnesses with more accuracy. In the future, while AI and ML will be used for patient improvement and data informatics will provide a better understanding of the disease. It can bring about a mechanism for patients to provide their clinicians with critical information to ensure the scope for better care. The big development on the healthcare landscape is the use of wearable devices which will gather the data of health and transmit it in real-time for faster treatment access. Wearables are designed for chronic condition monitoring.

Besides all these, the adoption of technology will also allow surveillance. These cover molecular markers where with AI and ML will see the physician understanding the disease. Besides, digital phenol-typing helps precise mapping leading to better diagnosis. All these as the paradigm shift in medicine as it will enhance patient empowered empathy, not progression of ageing and disease spread. All these transformations will give doctors time for themselves as diagnostics will be faster providing clarity on the disease progression.

All said and done, medical schools are playing a significant role in the deployment of AI in healthcare. They are incorporating AI courses into their curriculum and promoting research in this field. This will help produce a new generation of healthcare professionals who are familiar with AI and its applications in healthcare. Medical schools are also establishing partnerships with engineering colleges and start-ups to develop and test new AI-powered tools and systems. These partnerships provide students with practical experience working with AI technologies and can lead to the creation of new AI-powered solutions that can be used in clinical settings. By implementing AI technologies in clinical settings, medical schools are helping to accelerate the deployment of AI in healthcare.

While AI has the potential to revolutionize the field of medicine and improve patient outcomes, there are also potential concerns of bias, data privacy and security, clinical validity, interoperability, and ethical considerations.

The regulation and standardization of AI in medicine are still in their early stages, and there is a risk that the technology may be adopted and used before proper oversight is in place.

AI algorithms must be transparent and explainable so that healthcare professionals can understand how decisions are taken and ensure that they are fair and accurate.