AIMC Topic: Machine Learning

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A Machine Learning Approach with Human-AI Collaboration for Automated Classification of Patient Safety Event Reports: Algorithm Development and Validation Study.

JMIR human factors
BACKGROUND: Adverse events refer to incidents with potential or actual harm to patients in hospitals. These events are typically documented through patient safety event (PSE) reports, which consist of detailed narratives providing contextual informat...

Using slisemap to interpret physical data.

PloS one
Manifold visualisation techniques are commonly used to visualise high-dimensional datasets in physical sciences. In this paper, we apply a recently introduced manifold visualisation method, slisemap, on datasets from physics and chemistry. slisemap c...

Demystification of artificial intelligence for respiratory clinicians managing patients with obstructive lung diseases.

Expert review of respiratory medicine
INTRODUCTION: Asthma and chronic obstructive pulmonary disease (COPD) are leading causes of morbidity and mortality worldwide. Despite all available diagnostics and treatments, these conditions pose a significant individual, economic and social burde...

Machine learning can predict anterior elevation after reverse total shoulder arthroplasty: A new tool for daily outpatient clinic?

Musculoskeletal surgery
The aim of the present study was to individuate and compare specific machine learning algorithms that could predict postoperative anterior elevation score after reverse shoulder arthroplasty surgery at different time points. Data from 105 patients wh...

Novel gene signatures predicting and immune infiltration analysis in Parkinson's disease: based on combining random forest with artificial neural network.

Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology
BACKGROUND: Parkinson's disease (PD) ranks as the second most prevalent neurodegenerative disorder globally, and its incidence is rapidly rising. The diagnosis of PD relies on clinical characteristics. Although current treatments aim to alleviate sym...

Machine learning in the prediction of massive transfusion in trauma: a retrospective analysis as a proof-of-concept.

European journal of trauma and emergency surgery : official publication of the European Trauma Society
PURPOSE: Early administration and protocolization of massive hemorrhage protocols (MHP) has been associated with decreases in mortality, multiorgan system failure, and number of blood products used. Various prediction tools have been developed for th...

Multiparametric MRI model to predict molecular subtypes of breast cancer using Shapley additive explanations interpretability analysis.

Diagnostic and interventional imaging
PURPOSE: The purpose of this study was to assess the predictive performance of multiparametric magnetic resonance imaging (MRI) for molecular subtypes and interpret features using SHapley Additive exPlanations (SHAP) analysis.

Efficacy of stereotactic body radiotherapy and response prediction using artificial intelligence in oligometastatic gynaecologic cancer.

Gynecologic oncology
PURPOSE: We present a large real-world multicentric dataset of ovarian, uterine and cervical oligometastatic lesions treated with SBRT exploring efficacy and clinical outcomes. In addition, an exploratory machine learning analysis was performed.

The Promise and Perils of Artificial Intelligence in Health Professions Education Practice and Scholarship.

Academic medicine : journal of the Association of American Medical Colleges
Artificial intelligence (AI) methods, especially machine learning and natural language processing, are increasingly affecting health professions education (HPE), including the medical school application and selection processes, assessment, and schola...

Applications of Advanced Natural Language Processing for Clinical Pharmacology.

Clinical pharmacology and therapeutics
Natural language processing (NLP) is a branch of artificial intelligence, which combines computational linguistics, machine learning, and deep learning models to process human language. Although there is a surge in NLP usage across various industries...