AIMC Topic: Male

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Thessaly Graft Index: An Artificial Intelligence-Based Index for the Assessment of Graft Integrity in ACL-Reconstructed Knees.

The Journal of bone and joint surgery. American volume
BACKGROUND: Magnetic resonance imaging (MRI) has proven to be a valuable noninvasive tool to evaluate graft integrity after anterior cruciate ligament (ACL) reconstruction. However, MRI protocols and interpretation methodologies are quite diverse, pr...

Revolutionizing prostate cancer therapy: Artificial intelligence - Based nanocarriers for precision diagnosis and treatment.

Critical reviews in oncology/hematology
Prostate cancer is one of the major health challenges in the world and needs novel therapeutic approaches to overcome the limitations of conventional treatment. This review delineates the transformative potential of artificial intelligence (AL) in en...

The implementation of knowledge-based planning with partial OAR contours for prostate radiotherapy.

Journal of applied clinical medical physics
PURPOSE: Intra- and inter-observer contour uncertainty is a continuous challenge in treatment planning for radiotherapy. Our proposed solution to address this challenge is the use of partial contours for treatment planning, focusing on uninvolved or ...

Enhanced EEG-based cognitive workload detection using RADWT and machine learning.

Neuroscience
Understanding cognitive workload improves learning performance and provides insights into human cognitive processes. Estimating cognitive workload finds practical applications in adaptive learning systems, brain-computer interfaces, and cognitive mon...

Integration of radiomic and deep features to reliably differentiate benign renal lesions from renal cell carcinoma.

European journal of radiology
PURPOSE: Accurate differentiation of benign renal lesions from renal cell carcinoma (RCC) is crucial for optimized management, particularly for small renal lesions (≤4 cm in diameter). This study aimed to integrate clinical data, radiomic features, a...

Machine learning predicts selected cat diseases using insurance data amid challenges in interpretability.

American journal of veterinary research
OBJECTIVE: To develop models for prediction of the onset of specific diseases in cats using pet insurance data and to evaluate their predictive performance.

Diagnosis of Chronic Kidney Disease Using Retinal Imaging and Urine Dipstick Data: Multimodal Deep Learning Approach.

JMIR medical informatics
BACKGROUND: Chronic kidney disease (CKD) is a prevalent condition with significant global health implications. Early detection and management are critical to prevent disease progression and complications. Deep learning (DL) models using retinal image...

Development and Validation of a Machine Learning Algorithm for Predicting Diabetes Retinopathy in Patients With Type 2 Diabetes: Algorithm Development Study.

JMIR medical informatics
BACKGROUND: Diabetic retinopathy (DR) is the leading cause of preventable blindness worldwide. Machine learning (ML) systems can enhance DR in community-based screening. However, predictive power models for usability and performance are still being d...

Can muscle synergies shed light on the mechanisms underlying motor gains in response to robot-assisted gait training in children with cerebral palsy?

Journal of neuroengineering and rehabilitation
BACKGROUND: Children with cerebral palsy (CP) often experience gait impairments. Robot-assisted gait training (RGT) has been shown to have beneficial effects in this patient population. However, clinical outcomes of RGT vary substantially from patien...