Twenty years ago, IBM’s computer “Deep Blue” defeated world chess champion Garry Kasparov, which sparked much discussion, attention, and speculation. People also began to challenge Go, which was seen as the “pinnacle of intelligence,” but due to the barriers faced by computers, breakthroughs had not been achieved. From March 9 to March 15, 2016, in … Read more
In the traditional healthcare system, the tight resource situation is vividly reflected in the radiology department of hospitals. At three in the morning, in the quiet hospital, radiologists are still focused under dim lights, examining piles of CT scans, striving to identify tiny lung nodules that could mean life or death. This scene not only … Read more
Step-By-Step Guide to Building Clinical Prediction Models STEP 1 Purpose, Team, Review, and Plan 1 Clarify the Purpose of the Prediction Model Define the objectives of the prediction model, including: Target population: Specify the patient group the model is aimed at, such as HIV patients in South Africa, individuals with a history of diabetes, or … Read more
Paper Title: Capabilities of Gemini Models in Medicine Compiled by: Sienna Reviewed by: Los Healthcare is undoubtedly one of the fields that urgently needs disruption and innovation today. It accounts for nearly 10% of the Gross Domestic Product (GDP) on average, and in some specific contexts, such as the United States, this proportion even rises … Read more
AI healthcare tools are transforming the healthcare industry in unprecedented ways, changing patient care, clinical diagnosis, and management workflows. Research reports indicate that by 2030, the global AI healthcare tools market is expected to reach $20.82 billion, growing at a compound annual growth rate of 37.5% from 2023 to 2030. A survey by Stanford University … Read more
Editor’s Note With the rapid development of artificial intelligence technology, the health sector is continuously trying to improve the quality of medical care and enhance work efficiency by introducing AI. Due to the capability of large model technology to process large-scale data and perform complex tasks, it significantly enhances the generalization, versatility, and practicality of … Read more
Most applications of artificial intelligence in medicine utilize a single data modality to address tasks within a narrow scope, such as computed tomography (CT) scans or retinal photographs. However, clinicians integrate multi-source, multimodal data for diagnosis, prognosis assessment, and treatment planning. In this review, the authors explore the applications of multimodal datasets in healthcare, the … Read more
Human-AI collaboration refers to the interaction and cooperation between humans and artificial intelligence systems, aiming to leverage each other’s strengths to enhance work efficiency and decision-making quality. Humans possess creativity, emotion, and ethical judgment, while artificial intelligence excels in data processing, pattern recognition, and automation of tasks. Through collaboration, both can form a complementary relationship, … Read more
In 2030, will artificial intelligence drive economic growth, create breakthrough medical therapies, and simplify daily life as the data suggests? Or are these predictions overly optimistic: will artificial intelligence gradually fade away, or even make the world worse? Will artificial intelligence replace millions of jobs, replace human relationships, and challenge society with falsehoods? Recently, The … Read more
Click the blue words above to follow us, and click “Write a comment” at the end of the article to express your views. e-Medical Pang Tao The application of voice recognition technology at Peking University People’s Hospital (hereinafter referred to as “PKUPH”) began with the Radiology Department. As the first doctor to engage with and … Read more