Although overall physician salaries continue to rise steadily, the latest research reveals the caveats and complexities of physician compensation, such as a widening gender pay gap and vast differences between specialties. Published annually, the Medscape Physician Compensation Report is the most comprehensive and widely used physician salary survey in the United States, analyzing compensation, hours worked, time spent with patients, and what practitioners find the most rewarding and challenging about their jobs. Over 20,000 U.S. physicians across 30 specialties responded to this year’s online survey, delivering both good and bad news about the state of the healthcare system.
A growing body of research demonstrates significant discoveries and advancements in knowledge into potential biomedical strategies for reversing the aging process. Today, researchers continue to study animal and human abilities to regenerate cells, aiming to diminish cognitive decline, immune system weakening, and other adverse effects of the biological aging process. Meanwhile, healthcare and biotech companies race to “find the key” to reversing the aging process, bringing the market valuation of anti-aging medicine to a projected $610 billion by 2025 from current estimates of $110 billion. Investors are pouring millions into start-up companies that focus on anti-aging and regenerative medical research, in hopes of being the first organization to make a breakthrough – bringing a successful solution to aging to the public.
“We’re now in an era that some consider an AI renaissance, with enormous amounts of computing power — unimaginable only a few decades ago — now available to institutions and even individual researchers. Machine learning algorithms and AI are performing feats once considered to be exclusive domains for humans.” –Sushovan Guha, MD, PhD
In recent years, the prevalence of artificial intelligence (AI), machine learning (ML), and other breakthrough computer technologies has seen significant growth in medicine. Utilized by radiologists, neurologists, pathologists, and many other specialists, artificial intelligence has greatly expanded human capabilities and proved incredibly useful in parsing and aggregating enormous amounts of medical data. The ability to use this data to learn by itself and improve on its capabilities via machine learning has made AI a constantly self-evolving resource. Deep learning (DL) – a subset of ML – has shown exceptional performance in image analysis through its use of the convolutional neural network (CNN), adding to the growing list of AI applications in healthcare and gastroenterology specifically.