AIMC Topic: Humans

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Deep learning-based identification of patients at increased risk of cancer using routine laboratory markers.

Scientific reports
Early screening for cancer has proven to improve the survival rate and spare patients from intensive and costly treatments due to late diagnosis. Cancer screening in the healthy population involves an initial risk stratification step to determine the...

Driver facial emotion tracking using an enhanced residual network with weighted fusion of channel and spatial attention.

Scientific reports
Facial expression recognition (FER) plays a crucial role in interpreting human emotions and intentions in real-life applications, such as advanced driver assistance systems. However, it faces challenges due to subtle facial variations, environmental ...

Estimating gait parameters from sEMG signals using machine learning techniques under different power capacity of muscle.

Scientific reports
The gait analysis has been applied in many fields, such as the assessment of falling, force evaluation in sports, and gait disorder detection for neuromuscular diseases. Its main recording techniques include video cameras and wearable sensors. Howeve...

Machine learning-based differentiation of schizophrenia and bipolar disorder using multiscale fuzzy entropy and relative power from resting-state EEG.

Translational psychiatry
Schizophrenia (SZ) and bipolar disorder (BD) pose diagnostic challenges due to overlapping clinical symptoms and genetic factors, often resulting in misdiagnosis and suboptimal treatment outcomes. This study aimed to identify EEG-based biomarkers tha...

Remdesivir associated with reduced mortality in hospitalized COVID-19 patients: treatment effectiveness using real-world data and natural language processing.

BMC infectious diseases
BACKGROUND: Remdesivir (RDV) was the first antiviral approved for mild-to-moderate COVID-19 and for those patients at risk for progression to severe disease after clinical trials supported its association with improved outcomes. Real-world evidence (...

Kolmogorov-Arnold networks for predicting drug-gene associations of HDAC1 inhibitors in periodontitis.

Computational biology and chemistry
Periodontal disease, or periodontitis, is a chronic inflammatory condition affecting the tissues supporting teeth, with epigenetic mechanisms such as DNA methylation, histone modifications, and RNA molecules playing a crucial role in its progression....

Shear wave elastography values in endometrioma: Clinical findings and machine learning-based prediction models.

International journal of gynaecology and obstetrics: the official organ of the International Federation of Gynaecology and Obstetrics
OBJECTIVE: To evaluate the diagnostic value of shear wave elastography (SWE) in assessing endometriomas and its correlation with clinical symptoms. Furthermore, the study investigates the use of machine learning (ML) models to predict clinical outcom...