Engr. Dr. Muhammad Nawaz Iqbal
The field of healthcare is undergoing revolutionary changes due to the influence of artificial intelligence that entails shifts in diagnostics, therapeutic approaches, patient handling, and even the organizational structure of hospitals. In recent times, machine learning models have been trained on vast archives of medical records and imaging. They, therefore, enhance the diagnosis and evaluation of conditions such as, cancers, neurological and cardiovascular disorders quicker and sometimes more reliable than expert human diagnosticians. For example, with radiology algorithms, any tumor or fracture within the scans can be located with great accuracy. In addition, it uses historical data to recognize trends and predict outcomes for patients. This allows for intervention prior to the decline of patient’s condition. For instance, such algorithms help in identifying patients that are at increased risk of sepsis or worsening in the ICU enabling timely actions by the hospital.
Genetic data is employed with the aid of artificial intelligence algorithms in the development of personalized medicine such as cancer treatment based on a particular individual’s genetic data. AI interrogates the patient’s health record, and, taking into account other aspects such as history, lifestyle as well as genetic differences, recommends the best possible treatment. This method promotes clinical practice that is at the other end of the spectrum from the traditional ‘one size fits all’ model.” AI systems also facilitate the drug discovery process by determining which compounds have reduced efficacy in vitro, which saves several years from the drug development timeline. For example, AI can predict how a specific drug will bind to its target proteins. Using knowledge databases, AI can also repurpose several approved drugs for other issues, which is cheaper than developing a new one to address another problem.
AI approaches are used to optimize the scheduling of staff, management of beds, and inventory so that the necessary resources are available when and where they are required. Predictive models assist with forecasting demand which aids resource allocation. Administrative processes like scheduling, checking in patients, and billing can also be done by AI, therefore freeing up more time for nurses and doctors to take care of the patients. Other than that, chatbots and virtual assistants are being employed in patient engagement to facilitate seamless interaction with the information. Smart devices are able to track the heart rate, sleep duration, and physical activity of individuals allowing for monitoring of the individuals in real-time. Such devices employ AI to flag alerts to the doctors or caregivers whenever there are alarming changes. Also, with the help of NLP and computer vision, AI can be incorporated into a telehealth appointment by evaluating the patient’s symptoms and even their facial expressions for conducting diagnosis and post treatment checkup remotely.
AI is being utilized in Robotic surgical apparatuses to improve the performance of procedures regarding safety and efficiency, mostly in Minimally Invasive Surgeries. Furthermore, they can provide the surgeon with assistance by offering feedback and visualizing situations in more detail. Prosthetic limbs, as well as exoskeletons, that are powered by AI, follow the movements of their users, thus assisting the patients with physical disabilities in the process of moving and rehabilitation. Algorithm based natural language processing aids in quick transcription and understanding of soft clinical notes thereby reducing the number of hours the physicians dedicate for filling forms. They can also be able to make sense out of a large part of the medical records which is usually in an unshaped or free form and help the doctors find and analyze patient data more quickly. Tools powered by AI help such professionals gather more relevant information and keep treatments up-to-date with the best clinical evidence incorporating data from relevant texts such as medical literature, clinical guides, and patient documents.
NLP is used in digital platforms such as chatbots to implement cognitive behavioral therapy (CBT) exercises, track different mental health parameters, and provide support on a timely basis effectively dealing with the shortage of mental health providers. Algorithms can also recognize patterns in human voice, texts and even facial observations to signify depression or anxiety enabling intervention and constant supervision.
Heath care is being revolutionized by AI in such a way that healthcare providers are able to deliver care that is less time-consuming, more precise, and tailored to the specific patient population. With the advancement of AI technology, health care in the future will be proactive rather than being a responsive model with easy access to everyone and tailored to every individual’s preferences, though ethical, privacy and reliability issues will still be significant concerns.
