Coiera EW. Artificial Intelligence in Medicine: The Challenges Ahead. J of Am Med Informatics Assoc 1996; 3(6): 363-366. Click here to view the paper Abstract The modern study of artificial intelligence in medicine (AIM) is 25 years old. Throughout this period, the field has attracted many of the b
Ching T, Himmelstein DS, Beaulieu-Jones BK et al. Opportunities and Obstacles for Deep Learning in Biology and Medicine. J.R.Soc.Inteface 15:20170387. Click here to view the paper Abstract Deep learning describes a class of machine learning algorithms that are capable of combining raw inputs into l
Chen Y, Argentinis E, and Weber G. IBM Watson: How Cognitive Computing Can Be Applied to Big Data Challenges in Life Sciences Research. Clinical Therapeutics 2016; 38(4): 688-701. Abstract Life sciences researchers are under pressure to innovate faster than ever. Big data offer the promise of unlock
Chartrand G, Cheng PM, Vorontsov E et al. Deep Learning: A Primer for Radiologists. RadioGraphics 2017; 37(7): 2113-2131. Click here to view the paper Abstract Deep learning is a class of machine learning methods that are gaining success and attracting interest in many domains, including computer v
Char DS, Shah NH, and Magnus D. Implementing Machine Learning in Health care- Addressing Ethical Challenges. N Engl J Med 2018; 378(11): 981-983. Click here to view the paper The full list of the top 100 articles on artificial intelligence and artificial intelligence in medicine are published here:
Chang HY, Jung CK, Woo JI et al. Artificial Intelligence in Pathology. Journal of Pathology and Translational Medicine 2019; 53:1-12. Click here to view the paper Abstract As in other domains, artificial intelligence is becoming increasingly important in medicine. In particular, deep learning-based
Chang AC. Precision Intensive Care: A Real-Time Artificial Intelligence Strategy for the Future. Ped Crit Care Med 2019; 20(2): 194-195. Click here to view the paper The full list of the top 100 articles on artificial intelligence and artificial intelligence in medicine are published here: Intellig
Cabitza F, Locoro A, and Banfi G. Machine Learning in Orthopedics: A Literature Review. Frontiers in Bioengineering and Biotechnology 2018; 6:75. Click here to view the paper Summary In this paper we present the findings of a systematic literature review covering the articles published in the last
Bur AM, Shew M, and New J. Artificial Intelligence for the Otolaryngologist: A State of the Art Review. Otolaryngology-Head and Neck Surgery 2019; 160(4): 603-611. Click here to view the paper Objective To provide a state of the art review of artificial intelligence (AI), including its subfields of