User:Daspj/Artificial intelligence in healthcare/Bibliography

Pubmed search: https://pubmed.ncbi.nlm.nih.gov/?term=artificial%20intelligence%20medicine&filter=pubt.review&filter=pubt.systematicreview&filter=datesearch.y_1

Cardiovascular
Application of Artificial Intelligence in Cardiovascular Medicine - In this article, we provide an overview and discuss the current status of a wide range of AI applications, including machine learning, reinforcement learning, and deep learning, in cardiovascular medicine.

Application of Artificial Intelligence in Acute Coronary Syndrome: A Brief Literature Review - This paper is a review of the literature which will focus on the application of AI in ACS.

Harnessing artificial intelligence in cardiac rehabilitation, a systematic review - Incorporation of AI into healthcare, cardiac rehabilitation delivery, and monitoring holds great potential for early detection of cardiac events, allowing for home-based monitoring, and improved clinician decision making.

Radiogenomics and Artificial Intelligence Approaches Applied to Cardiac Computed Tomography Angiography and Cardiac Magnetic Resonance for Precision Medicine in Coronary Heart Disease: A Systematic Review

Social Determinants in Machine Learning Cardiovascular Disease Prediction Models: A Systematic Review

Deep Learning Methods for Heart Sounds Classification: A Systematic Review

Applications of machine learning to undifferentiated chest pain in the emergency department: A systematic review

Machine learning for subtype definition and risk prediction in heart failure, acute coronary syndromes and atrial fibrillation: systematic review of validity and clinical utility

Gastroenterology
Applications of artificial intelligence (AI) in researches on non-alcoholic fatty liver disease(NAFLD) : A systematic review -

Infectious diseases
Role of Artificial Intelligence in COVID-19 Detection -

Oncology
Artificial Intelligence in Cancer Research and Precision Medicine - Here, we review the recent enormous progress in the application of AI to oncology, highlight limitations and pitfalls, and chart a path for adoption of AI in the cancer clinic.

Ophthalmology
Digital technology, tele-medicine and artificial intelligence in ophthalmology: A global perspective - The review summarises the digital strategies that countries are developing and discusses technologies that may increasingly enter the clinical workflow and processes of ophthalmologists.

Radiology
Artificial Intelligence and Machine Learning in Nuclear Medicine: Future Perspectives

Sleep medicine
Artificial intelligence and sleep: Advancing sleep medicine - We review examples of AI use in screening, endotyping, diagnosing, and treating sleep disorders and place this in the context of precision/personalized sleep medicine. We explore the opportunities for AI to both facilitate and extend providers' clinical impact and present ethical considerations regarding AI derived prognostic information. We cover early adopting specialties of AI in the clinical realm, such as radiology and pathology, to provide a road map for the challenges sleep medicine is likely to face when deploying this technology. Finally, we discuss pitfalls to ensure clinical AI implementation proceeds in the safest and most effective manner possible.

Urology
Artificial intelligence in bladder cancer prognosis: a pathway for personalized medicine -

Disease diagnosis
Preventing sepsis; how can artificial intelligence inform the clinical decision-making process? A systematic review -

Creation of new drugs
Artificial intelligence in early drug discovery enabling precision medicine