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Dietary Assessment With Multimodal ChatGPT: A Systematic Analysis.

IEEE journal of biomedical and health informatics
Conventional approaches to dietary assessment are primarily grounded in self-reporting methods or structured interviews conducted under the supervision of dietitians. These methods, however, are often subjective, inaccurate, and time-intensive. Altho...

In-Home Gait Abnormality Detection Through Footstep-Induced Floor Vibration Sensing and Person-Invariant Contrastive Learning.

IEEE journal of biomedical and health informatics
Detecting gait abnormalities is crucial for assessing fall risks and early identification of neuromusculoskeletal disorders such as Parkinson's and stroke. Traditional assessments in gait clinics are infrequent and pose barriers, particularly for dis...

Care home resident identification: A comparison of address matching methods with Natural Language Processing.

PloS one
BACKGROUND: Care home residents are a highly vulnerable group, but identifying care home residents in routine data is challenging. This study aimed to develop and validate Natural Language Processing (NLP) methods to identify care home residents from...

Comparing effects of wearable robot-assisted gait training on functional changes and neuroplasticity: A preliminary study.

PloS one
Robot-assisted gait training (RAGT) is a promising technique for improving the gait ability of elderly adults and patients with gait disorders by enabling high-intensive and task-specific training. Gait functions involve multiple brain regions and ne...

Ethical attitudes and perspectives of AI use in medicine between Croatian and Slovenian faculty members of school of medicine: Cross-sectional study.

PloS one
BACKGROUND: Artificial intelligence (AI) is present in preclinical, clinical and research work, in various branches of medicine. Researchers and teachers at school of medicines may have different ethical attitudes and perspectives about the implement...

Machine-learning-based identification of patients with IgA nephropathy using a computerized medical billing database.

PloS one
The billing database of the universal healthcare system in Japan potentially includes large-cohort data of patients with immunoglobulin A nephropathy, diagnosis codes aimed at billing should not be directly used for clinical research because of the r...

A machine-learning model for prediction of Acinetobacter baumannii hospital acquired infection.

PloS one
BACKGROUND: Acinetobacter baumanni infection is a leading cause of morbidity and mortality in the Intensive Care Unit (ICU). Early recognition of patients at risk for infection allows early proper treatment and is associated with improved outcomes. T...

Understanding veterinary practitioners' responses to adverse events using a combined grounded theory and netnographic natural language processing approach.

PloS one
Support that mitigates the detrimental impact of adverse events on human healthcare practitioners is underpinned by an understanding of their experiences. This study used a mixed methods approach to understand veterinary practitioners' responses to a...

Enhancing ergonomics in E-waste disassembly: the impact of collaborative robotics on muscle activation and coordination.

Ergonomics
Disassembly, as a part of the electronic waste (e-waste) management process, is a labour-intensive task. The emergence of collaborative robots (cobots) provides a robotic solution to reduce the human efforts during disassembly. This study evaluated m...

Predicting progression-free survival in sarcoma using MRI-based automatic segmentation models and radiomics nomograms: a preliminary multicenter study.

Skeletal radiology
OBJECTIVES: Some sarcomas are highly malignant, associated with high recurrence despite treatment. This multicenter study aimed to develop and validate a radiomics signature to estimate sarcoma progression-free survival (PFS).