AIMC Topic: Humans

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Machine learning models for classifying non-specific neck pain using craniocervical posture and movement.

Musculoskeletal science & practice
OBJECTIVE: Physical therapists and clinicians commonly confirm craniocervical posture (CCP), cervical retraction, and craniocervical flexion as screening tests because they contribute to non-specific neck pain (NSNP). We compared the predictive perfo...

SNSynergy: Similarity network-based machine learning framework for synergy prediction towards new cell lines and new anticancer drug combinations.

Computational biology and chemistry
The computational method has been proven to be a promising means for pre-screening large-scale anticancer drug combinations to support precision oncology applications. Pioneering efforts have been made to develop machine learning technology for predi...

Comparative analysis of image quality and interchangeability between standard and deep learning-reconstructed T2-weighted spine MRI.

Magnetic resonance imaging
RATIONALE AND OBJECTIVES: MRI reconstruction of undersampled data using a deep learning (DL) network has been recently performed as part of accelerated imaging. Herein, we compared DL-reconstructed T2-weighted image (T2-WI) to conventional T2-WI rega...

Artificial Intelligence for Lamellar Keratoplasty.

Klinische Monatsblatter fur Augenheilkunde
The training of artificial intelligence (AI) is becoming increasingly popular. More and more studies on lamellar keratoplasty are also being published. In particular, the possibility of non-invasive and high-resolution imaging technology of optical c...

Screening/diagnosis of pediatric endocrine disorders through the artificial intelligence model in different language settings.

European journal of pediatrics
UNLABELLED: This study is aimed at examining the impact of ChatGPT on pediatric endocrine and metabolic conditions, particularly in the areas of screening and diagnosis, in both Chinese and English modes. A 40-question questionnaire covering the four...

Practical use case of natural language processing for observational clinical research data retrieval from electronic health records: AssistMED project.

Polish archives of internal medicine
INTRODUCTION: Electronic health records (EHRs) contain data valuable for clinical research. However, they are in textual format and require manual encoding to databases, which is a lengthy and costly process. Natural language processing (NLP) is a co...

A machine learning approach to predict daptomycin exposure from two concentrations based on Monte Carlo simulations.

Antimicrobial agents and chemotherapy
Daptomycin is a concentration-dependent lipopeptide antibiotic for which exposure/effect relationships have been shown. Machine learning (ML) algorithms, developed to predict the individual exposure to drugs, have shown very good performances in comp...