Deep learning has already shown tremendous potential in improving healthcare in various ways, and additional advancements and applications of deep learning arise on an ongoing basis in the field of healthcare. This interesting news came to us from EurekAlert! in their article, “Deep learning method developed to understand how chronic pain affects each patient’s body.

One research team has carried out a study to analyze how chronic pain affects each patient’s body. Within this framework, a deep learning method has been developed to analyze the biometric data of people with chronic conditions.

Deep learning models have been employed to diagnose various diseases, including cancer, neurological disorders, and cardiovascular conditions. They can analyze large-scale patient data, electronic health records (EHRs), and medical histories to predict disease risk and assist in early intervention with preventive care.

While deep learning has shown great promise in healthcare, there are still challenges to overcome, including information privacy concerns, regulatory compliance, and the need for interpretability and explainability in the models’ decisions. Despite these challenges, ongoing research and advancements in deep learning continue to shape a brighter future for healthcare, with the potential to revolutionize patient care and medical practices.

The real challenge is that most organizations have little knowledge on how artificial intelligence (AI) systems make decisions. Explainable AI allows users to comprehend and trust the results and output created by machine learning algorithms.

Melody K. Smith

Data Harmony is an award-winning semantic suite that leverages explainable AI.

Sponsored by Access Innovations, the intelligence and the technology behind world-class explainable AI solutions.