AIMC Topic: Humans

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Machine learning combine with nomogram to guide the establishment of endoscopic assistant system for gasless transaxillary endoscopic thyroidectomy.

Annals of medicine
OBJECTIVE: To explore the influence related factors of endoscopic assistant in gasless transaxillary endoscopic thyroidectomy by using machine learning and nomogram, and construct an endoscopic assistant system.

Development and validation of MRI-based radiomics model for clinical symptom stratification of extrinsic adenomyosis.

Annals of medicine
BACKGROUND: Extrinsic adenomyosis exhibits heterogeneous clinical symptoms, with pain being more commonly reported. The relationship between magnetic resonance imaging (MRI) feature and symptom remains unclear.

Unraveling the sensory metabolome of blueberries: An integrated metabolomics and machine learning approach across cultivars and geographical origins.

Food chemistry
Consumer-driven blueberry quality improvement requires a deeper understanding of how metabolic composition influences sensory perception. This study integrates untargeted metabolomics and machine learning to identify biomarker metabolites shaping sen...

A dual-view deep learning-driven discovery of cinnamoyl anthranilic acid derivatives against orthopoxvirus through targeting host ITGB3.

European journal of medicinal chemistry
The orthopoxvirus genus, particularly the monkeypox virus (MPXV), continues to pose a significant global public health threat. Therefore, the development of novel anti-orthopoxvirus agents remains an urgent priority. Machine learning has proven to be...

Leveraging readily available clinical data with machine learning to predict first-line immunotherapy outcomes in non-small cell lung cancer.

International immunopharmacology
BACKGROUND: Immune checkpoint inhibitors (ICIs) are essential first-line treatments for recurrent or metastatic non-small cell lung cancer (NSCLC). However, predicting their effectiveness and the occurrence of immunotherapy-related adverse events (ir...

A hyperspectral imaging dataset and Grassmann manifold method for intraoperative pixel-wise classification of metastatic colon cancer in the liver.

Computers in biology and medicine
Hyperspectral imaging (HSI) holds significant potential for transforming the field of computational pathology. However, the number of HSI-based research studies remains limited, and in many cases, the advantages of HSI over traditional RGB imaging ha...

Benchmarking of open-source algorithms for heart rate estimation from motion-corrupted photoplethysmography.

Computers in biology and medicine
Photoplethysmography holds promise for continuous, non-intrusive heart rate monitoring through wearable devices. However, motion artifacts can impact the reliability of heart rate estimates. The integration of accelerometer data has been proven helpf...

Interpretable multi-variable transformer network for regional-level short-term bicycle crash risk prediction.

Accident; analysis and prevention
Effective short-term prediction of bicycle crashes at the urban regional level is critical for proactive infrastructure safety interventions and data-driven traffic management. However, three key challenges persist: (1) inadequate modeling of complex...

Artificial Intelligence in Health Profession Education.

Indian pediatrics
Artificial Intelligence (AI) is rapidly integrating into medicine, demanding that Health Professional Education (HPE) incorporates AI literacy to prepare future clinicians. AI is driving transformative changes across all sectors. In education, it ena...

Genetic analyses of eight complex diseases using predicted continuous representations of disease.

Cell reports methods
We evaluated whether predicted continuous disease representations could enhance genetic discovery beyond case-control genome-wide association study (GWAS) phenotypes across eight complex diseases in up to 485,448 UK Biobank participants. Predicted ph...