AIMC Topic: Male

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Epilepsy surgery candidate identification with artificial intelligence: An implementation study.

Journal of clinical neuroscience : official journal of the Neurosurgical Society of Australasia
BACKGROUND: To (a) evaluate the effect of a machine learning algorithm in the identification of patients suitable for epilepsy surgery evaluation, and (b) examine the performance of a large language model (LLM) in the collation of key pieces of infor...

Explaining Human Activity Recognition with SHAP: Validating insights with perturbation and quantitative measures.

Computers in biology and medicine
In Human Activity Recognition (HAR), understanding the intricacy of body movements within high-risk applications is essential. This study uses SHapley Additive exPlanations (SHAP) to explain the decision-making process of Graph Convolution Networks (...

AI-MET: A deep learning-based clinical decision support system for distinguishing multisystem inflammatory syndrome in children from endemic typhus.

Computers in biology and medicine
The COVID-19 pandemic brought several diagnostic challenges, including the post-infectious sequelae multisystem inflammatory syndrome in children (MIS-C). Some of the clinical features of this syndrome can be found in other pathologies such as Kawasa...

Multimodal Artificial Intelligence-Based Virtual Biopsy for Diagnosing Abdominal Lavage Cytology-Positive Gastric Cancer.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Gastric cancer with peritoneal dissemination remains a significant clinical challenge due to its poor prognosis and difficulty in early detection. This study introduces a multimodal artificial intelligence-based risk stratification assessment (RSA) m...

Machine Learning Techniques for Simulating Human Psychophysical Testing of Low-Resolution Phosphene Face Images in Artificial Vision.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)
To evaluate the quality of artificial visual percepts generated by emerging methodologies, researchers often rely on labor-intensive and tedious human psychophysical experiments. These experiments necessitate repeated iterations upon any major/minor ...

Unveiling the effect of urinary xenoestrogens on chronic kidney disease in adults: A machine learning model.

Ecotoxicology and environmental safety
Exposure to three primary xenoestrogens (XEs), including phthalates, parabens, and phenols, has been strongly associated with chronic kidney disease (CKD). An interpretable machine learning (ML) model was developed to predict CKD using data from the ...

Deep Learning-Based Tumor Segmentation of Murine Magnetic Resonance Images of Prostate Cancer Patient-Derived Xenografts.

Tomography (Ann Arbor, Mich.)
BACKGROUND/OBJECTIVE: Longitudinal in vivo studies of murine xenograft models are widely utilized in oncology to study cancer biology and develop therapies. Magnetic resonance imaging (MRI) of these tumors is an invaluable tool for monitoring tumor g...

Investigation of Trajectory Tracking Control in Hip Joints of Lower-Limb Exoskeletons Using SSA-Fuzzy PID Optimization.

Sensors (Basel, Switzerland)
The application of lower-limb exoskeleton robots in rehabilitation is becoming more prevalent, where the precision of control and the speed of response are essential for effective movement tracking. This study tackles the challenge of optimizing both...

Application of causal forests to randomised controlled trial data to identify heterogeneous treatment effects: a case study.

BMC medical research methodology
BACKGROUND: Classical approaches to subgroup analysis in randomised controlled trials (RCTs) to identify heterogeneous treatment effects (HTEs) involve testing the interaction between each pre-specified possible treatment effect modifier and the trea...

Feasibility study of texture-based machine learning approach for early detection of neonatal jaundice.

Scientific reports
Untreated neonatal jaundice can have severe consequences. Effective screening for neonatal jaundice can prevent long-term complications in infants. Non-invasive approaches may be beneficial in settings with limited resources. This feasibility study e...