AIMC Topic: Male

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D-amphetamine alters the dynamic ECoG activity distribution patterns in the rat neocortex.

Scientific reports
Amphetamine has widespread effects on multiple neurotransmitter systems, potentially altering the physiological connectivity and network dynamics across various regions of the brain. In this study, we investigated the effects of D-amphetamine using o...

Development and validation of an interpretable machine learning model for early prediction in patients with diabetes and sepsis.

Scientific reports
We aimed to identify and validate key predictive factors influencing 28-day survival rates in patients with diabetes and sepsis and to develop a predictive model based on these factors to assist clinical decision-making. In this retrospective cohort ...

Artificial intelligence-based method for detecting wrist fractures in children.

Scientific reports
Pediatric wrist fractures are common skeletal injuries in clinical practice; however, due to the ongoing development of children's bones, fracture characteristics are complex and often prone to misdiagnosis or missed diagnosis. Moreover, traditional ...

The Genetic Architecture of the Human Corpus Callosum and its Subregions.

Nature communications
The corpus callosum (CC) is the largest set of white matter fibers connecting the two hemispheres of the brain. In humans, it is essential for coordinating sensorimotor responses and performing associative or executive functions. Identifying which ge...

Prognostic prediction in soft-tissue sarcomas using deep learning and digital pathology of tumor and margin areas.

Scientific reports
The histological FNCLCC grade is the primary prognostic factor in soft-tissue sarcoma (STS) but fails to fully capture high risk patients. This study aimed to develop and validate a deep learning (DL) model to predict metastatic relapse-free survival...

Interpretable radiomics-based machine learning model for differentiating glioblastoma from primary central nervous system lymphoma using contrast-enhanced T1-weighted imaging.

Scientific reports
This study aimed to develop and validate an interpretable radiomics-based machine learning model using contrast-enhanced T1-weighted imaging (CE-T1WI) to differentiate glioblastoma (GB) from primary central nervous system lymphoma (PCNSL), while comp...

Quantitative Assessment of Strabismus Using Cloud AI Computing: Validation Study.

JMIR formative research
BACKGROUND: Strabismus measurement is essential in vision assessment and screening. It typically requires skilled clinicians or specialized equipment. Photographic strabismus measurement methods have value in terms of accessibility and convenience of...

Deep learning-based non-invasive differential diagnosis of eyelid basal cell and sebaceous gland carcinomas using photographic images.

International ophthalmology
PURPOSE: Pathological examination, the current gold standard for differentiating eyelid basal cell carcinoma (BCC) and sebaceous gland carcinoma (SGC), is invasive, time-consuming, and often inaccessible in primary care hospitals. Therefore, a non-in...

AI-based approach for heart failure readmission prediction using SCG, ECG, and GSR signals.

Physiological measurement
Heart failure (HF) is considered a global pandemic because of increasing prevalence, high mortality rate, frequent hospitalization, and associated economic burden. This study explores a noninvasive method that may help in managing HF patients by pred...

Analysis of sperm beating characteristics using microfluidic trapping and machine-learning-based flagellum tracking.

Lab on a chip
Male infertility affects a significant portion of couples worldwide, with standard semen analysis often failing to identify functional deficiencies in sperm performance. This study presents a microfluidic platform for characterizing sperm flagellar b...