AIMC Topic: Female

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UNIK (Urologic Non-Neoplastic Investigation of Kidneys): a machine learning approach to decode benign lesion.

World journal of urology
PURPOSE: Predicting the likelihood of benign neoplasia in patients with suspected renal cell carcinoma (RCC) is a cornerstone of presurgical planning. We sought to create and validate U.N.I.K., a machine learning (ML) model capable of predicting beni...

Machine learning models for predicting severe acute kidney injury in patients with sepsis-induced myocardial injury.

Scientific reports
Severe acute kidney injury (sAKI) is a prevalent and serious complication among patients with sepsis-induced myocardial injury (SIMI). Prompt and early prediction of sAKI has an important role in timely intervention, ultimately improving the patients...

Identification of key proteins and pathways in myocardial infarction using machine learning approaches.

Scientific reports
Acute myocardial infarction (AMI) is a leading cause of global morbidity and mortality, requiring deeper insights into its molecular mechanisms for improved diagnosis and treatment. This study combines proteomics, transcriptomics and machine learning...

Advancing prenatal healthcare by explainable AI enhanced fetal ultrasound image segmentation using U-Net++ with attention mechanisms.

Scientific reports
Prenatal healthcare development requires accurate automated techniques for fetal ultrasound image segmentation. This approach allows standardized evaluation of fetal development by minimizing time-exhaustive processes that perform poorly due to human...

Development of a machine learning-based model to predict urethral recurrence following radical cystectomy: a multicentre retrospective study and updated meta-analysis.

Scientific reports
Urethral recurrence (UR) following radical cystectomy for bladder cancer represents an aggressive disease failure with typically poor survival outcomes. Our study aimed to assess the predictive risk factors for UR, to develop and validate an easy-to-...

Predicting breast self-examination awareness in Sub-Saharan Africa using machine learning.

Scientific reports
Breast self-examination is a very cost-reducing approach that significantly decreases the cost burdens associated with medical equipment, fees of healthcare practitioners, transportation to health facilities, and other indirect costs. Furthermore, it...

Automated interpretation of cardiotocography using deep learning in a nationwide multicenter study.

Scientific reports
Timely detection of abnormal cardiotocography (CTG) during labor plays a crucial role in enhancing fetal prognosis. Recent research has explored the use of deep learning for CTG interpretation, most studies rely on small, localized datasets or focus ...

Digital removal of dermal denticle layer using geometric AI from 3D CT scans of shark craniofacial structures enhances anatomical precision.

Scientific reports
Craniofacial morphometrics in sharks provide crucial insights into evolutionary history, geographical variation, sexual dimorphism, and developmental patterns. However, the fragile cartilaginous nature of shark craniofacial skeleton poses significant...

Clinical Management of Wasp Stings Using Large Language Models: Cross-Sectional Evaluation Study.

Journal of medical Internet research
BACKGROUND: Wasp stings are a significant public health concern in many parts of the world, particularly in tropical and subtropical regions. The venom of wasps contains a variety of bioactive compounds that can lead to a wide range of clinical effec...

Integrating Nurse Preferences Into AI-Based Scheduling Systems: Qualitative Study.

JMIR formative research
BACKGROUND: Nurse scheduling is a complex challenge in health care, impacting both patient care quality and nurse well-being. Traditional scheduling methods often fail to consider individual preferences, leading to dissatisfaction, burnout, and high ...