In her first year at the David Geffen School of Medicine at UCLA, Katharina "Kat" Schmolly, MD, heard an old saying: "When you hear hoofbeats, think of horses, not zebras."
Jul 3, 2024
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An algorithm can help health care professionals recognize which patients have a highly aggressive form of basal cell carcinoma (BCC) of the face. If more BCCs are correctly identified as high-risk, the patients can directly ...
Jul 2, 2024
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Artificial intelligence (AI), machine learning (ML), and deep learning (DL) are increasingly transforming the medical field by enhancing diagnostic accuracy, prognostic predictions, precision treatments, and operational efficiency ...
Jul 2, 2024
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As patients with lung cancer live longer, the risk of long-term cardiac side effects of radiation therapy has been increasing, despite advances that reduce the radiation dose to the heart. New research uses machine learning ...
Jun 27, 2024
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An article recently published in The Journal of Rheumatology by UK Health care's Jagannadha (Jay) Avasarala, M.D., Ph.D., professor of neurology, outlines the promise of point of care ultrasound (POCUS) in the diagnosis of ...
Jun 26, 2024
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Soft tissue sarcomas (STSs) represent a diverse group of tumors that pose significant diagnostic and therapeutic challenges. In a recent review published in the journal Meta-Radiology, a team of researchers from The Second ...
Jun 20, 2024
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In a new UCLA-led study, investigators shed light on the intricate processes underlying cancer evolution and define the optimal algorithms to analyze the genetic makeup of tumors.
Jun 11, 2024
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A Johns Hopkins University-led research team has designed a method to generate enormous datasets of artificial, automatically annotated liver tumors on CT scans, enabling artificial intelligence models to be trained to accurately ...
May 31, 2024
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In the realm of gastrointestinal (GI) endoscopy, artificial intelligence (AI) is becoming an essential tool, especially in the computer-aided detection of precancerous colon polyps during screening colonoscopy. This integration ...
May 23, 2024
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The clumping of proteins is at the root of a wide range of neurodegenerative disorders that affect the brain, such as Alzheimer's and dementia. Researchers at the University of Copenhagen have developed a new tool that can ...
May 22, 2024
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In mathematics, computing, linguistics, and related subjects, an algorithm is a finite sequence of instructions, an explicit, step-by-step procedure for solving a problem, often used for calculation and data processing. It is formally a type of effective method in which a list of well-defined instructions for completing a task, will when given an initial state, proceed through a well-defined series of successive states, eventually terminating in an end-state. The transition from one state to the next is not necessarily deterministic; some algorithms, known as probabilistic algorithms, incorporate randomness.
A partial formalization of the concept began with attempts to solve the Entscheidungsproblem (the "decision problem") posed by David Hilbert in 1928. Subsequent formalizations were framed as attempts to define "effective calculability" (Kleene 1943:274) or "effective method" (Rosser 1939:225); those formalizations included the Gödel-Herbrand-Kleene recursive functions of 1930, 1934 and 1935, Alonzo Church's lambda calculus of 1936, Emil Post's "Formulation 1" of 1936, and Alan Turing's Turing machines of 1936–7 and 1939.
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