AIMC Topic: Humans

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Editorial Commentary: The Scope of Medical Research Concerning ChatGPT Remains Limited by Lack of Originality.

Arthroscopy : the journal of arthroscopic & related surgery : official publication of the Arthroscopy Association of North America and the International Arthroscopy Association
There is no shortage of literature surrounding ChatGPT and whether this large language model can provide accurate and clinically relevant information in response to simulated patient queries. Unfortunately, there is a shortage of literature addressin...

Prediction model for major bleeding in anticoagulated patients with cancer-associated venous thromboembolism using machine learning and natural language processing.

Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico
PURPOSE: We developed a predictive model to assess the risk of major bleeding (MB) within 6 months of primary venous thromboembolism (VTE) in cancer patients receiving anticoagulant treatment. We also sought to describe the prevalence and incidence o...

Deep Learning-Based Blood Abnormalities Detection as a Tool for VEXAS Syndrome Screening.

International journal of laboratory hematology
INTRODUCTION: VEXAS is a syndrome described in 2020, caused by mutations of the UBA1 gene, and displaying a large pleomorphic array of clinical and hematological features. Nevertheless, these criteria lack significance to discriminate VEXAS from othe...

Deep-learning-assisted thermogalvanic hydrogel fiber sensor for self-powered in-nostril respiratory monitoring.

Journal of colloid and interface science
Direct and consistent monitoring of respiratory patterns is crucial for disease prognostication. Although the wired clinical respiratory monitoring apparatus can operate accurately, the existing defects are evident, such as the indispensability of an...

Identification of mitophagy-related genes and analysis of immune infiltration in the astrocytes based on machine learning in the pathogenesis of major depressive disorder.

Journal of affective disorders
BACKGROUNDS: Major depressive disorder (MDD) is a pervasive mental and mood disorder with complicated and heterogeneous etiology. Mitophagy, a selective autophagy of cells, specifically eliminates dysfunctional mitochondria. The mitochondria dysfunct...

Radiomics machine learning algorithm facilitates detection of small pancreatic neuroendocrine tumors on CT.

Diagnostic and interventional imaging
PURPOSE: The purpose of this study was to develop a radiomics-based algorithm to identify small pancreatic neuroendocrine tumors (PanNETs) on CT and evaluate its robustness across manual and automated segmentations, exploring the feasibility of autom...

Machine learning with multiple modalities of brain magnetic resonance imaging data to identify the presence of bipolar disorder.

Journal of affective disorders
BACKGROUND: Bipolar disorder (BD) is a chronic psychiatric mood disorder that is solely diagnosed based on clinical symptoms. These symptoms often overlap with other psychiatric disorders. Efforts to use machine learning (ML) to create predictive mod...

The concept that went viral: Using machine learning to discover charisma in the wild.

The British journal of sociology
The term "charisma" is recognized as sociology's most successful export to common speech. While sociologists habitually dismiss popular uses of the word, we address its vernacularity head on as a worthy object of study and as a potential resource for...