AIMC Topic: Machine Learning

Clear Filters Showing 6241 to 6250 of 34417 articles

A Systematic Review of Features Forecasting Patient Arrival Numbers.

Computers, informatics, nursing : CIN
Adequate nurse staffing is crucial for quality healthcare, necessitating accurate predictions of patient arrival rates. These forecasts can be determined using supervised machine learning methods. Optimization of machine learning methods is largely a...

A machine learning model utilizing Delphian lymph node characteristics to predict contralateral central lymph node metastasis in papillary thyroid carcinoma: a prospective multicenter study.

International journal of surgery (London, England)
BACKGROUND: This study aimed to use artificial intelligence (AI) to integrate various radiological and clinical pathological data to identify effective predictors of contralateral central lymph node metastasis (CCLNM) in patients with papillary thyro...

Prediction of sepsis among patients with major trauma using artificial intelligence: a multicenter validated cohort study.

International journal of surgery (London, England)
BACKGROUND: Sepsis remains a significant challenge in patients with major trauma in the ICU. Early detection and treatment are crucial for improving outcomes and reducing mortality rates. Nonetheless, clinical tools for predicting sepsis among patien...

Identification of a gene score related to antigen processing and presentation machinery for predicting prognosis in head and neck squamous cell carcinoma and its potential implications for immunotherapy.

Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico
BACKGROUND: Despite its crucial role in immune surveillance and cell survival of tumors, the significance of MHC antigen processing and presentation machinery (APM) is still not fully understood in head and neck squamous cell carcinoma (HNSCC). We so...

Predicting Discharge Destination From Inpatient Rehabilitation Using Machine Learning.

American journal of physical medicine & rehabilitation
Predicting discharge destination for patients at inpatient rehabilitation facilities is important as it facilitates transitions of care and can improve healthcare resource utilization. This study aims to build on previous studies investigating discha...

Machine learning outperforms humans in microplastic characterization and reveals human labelling errors in FTIR data.

Journal of hazardous materials
Microplastics are ubiquitous and appear to be harmful, however, the full extent to which these inflict harm has not been fully elucidated. Analysing environmental sample data is challenging, as the complexity in real data makes both automated and man...

Machine learning identifies remodeling patterns in human lung extracellular matrix.

Acta biomaterialia
Organ function depends on the three-dimensional integrity of the extracellular matrix (ECM). The structure resulting from the location and association of ECM components is a central regulator of cell behavior, but a dearth of matrix-specific analysis...

Knowledge domain and frontier trends of artificial intelligence applied in solid organ transplantation: A visualization analysis.

International journal of medical informatics
BACKGROUND: Solid organ transplantation (SOT) is vital for end-stage organ failure but faces challenges like organ shortage and rejection. Artificial intelligence (AI) offers potential to improve outcomes through better matching, success prediction, ...

Machine Learning-Based Pathomics Model Predicts Angiopoietin-2 Expression and Prognosis in Hepatocellular Carcinoma.

The American journal of pathology
Angiopoietin-2 (ANGPT2) shows promise as prognostic marker and therapeutic target in hepatocellular carcinoma (HCC). However, assessing ANGPT2 expression and prognostic potential using histopathology images viewed with naked eye is challenging. Herei...

Nutrient based classification of Phyllospora comosa biomasses using machine learning algorithms: Towards sustainable valorisation.

Food research international (Ottawa, Ont.)
Sustainable seaweed value chains necessitate accurate biomass biochemical characterisation that leads to product development, geographical authentications and quality and sustainability assurances. Underutilised yet abundantly available seaweed speci...