AI in Healthcare : Diagnosis and Patient Monitoring

The adoption of Artificial Intelligence (AI) as an element of medical procedures has transitioned from a mere disruption to become a fundamental part of today's practice. The current research paper addresses how AI revolutionizes the healthcare industry, namely, automated diagnoses and real-time patient monitoring. The utilization of neural network models to analyze imaging via CNNs and time series data using Transformers proves that, indeed, AI is capable of diagnosing patients at least as well as human specialists in areas such as radiology and pathology. Moreover, this paper sheds light on the move from traditional approaches to treatment to the concept of Remote Patient Monitoring (RPM) enabled by advanced AI wearables and contactless sensors, which are capable of predicting a clinical deterioration in a patient's health up to 16 hours before any symptoms emerge. However, despite the impressive capabilities demonstrated, the opacity of neural networks and algorithmic biases remain significant obstacles to establishing the ubiquitous trust. Therefore, one can conclude that AI greatly decreases diagnostic delay and eliminates clinician's stress, yet the future of the industry lies in XAI solutions and federated learning systems.