AIMC Topic: Male

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Non-invasive physiological assessment of intermediate coronary stenoses from plain angiography through artificial intelligence: the STARFLOW system.

European heart journal. Quality of care & clinical outcomes
BACKGROUND: Despite evidence supporting use of fractional flow reserve (FFR) and instantaneous waves-free ratio (iFR) to improve outcome of patients undergoing coronary angiography (CA) and percutaneous coronary intervention, such techniques are stil...

Incidence trends, overall survival, and metastasis prediction using multiple machine learning and deep learning techniques in pediatric and adolescent population with osteosarcoma and Ewing's sarcoma: nomogram and webpage.

Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico
OBJECTIVE: The objective of this study was to analyze the incidence and overall survival (OS) of osteosarcoma (OSC) and Ewing's sarcoma (EWS) in a pediatric and adolescent population, employing machine learning (ML) and deep learning (DL) models to p...

An Integrated Electroencephalography and Eye-Tracking Analysis Using eXtreme Gradient Boosting for Mental Workload Evaluation in Surgery.

Human factors
ObjectiveWe aimed to develop advanced machine learning models using electroencephalogram (EEG) and eye-tracking data to predict the mental workload associated with engaging in various surgical tasks.BackgroundTraditional methods of evaluating mental ...

Development and Evaluation of an Automated Protocol Recommendation System for Chest CT Using Natural Language Processing With CLEVER Terminology Word Replacement.

Canadian Association of Radiologists journal = Journal l'Association canadienne des radiologistes
To evaluate the clinical performance of a Protocol Recommendation System (PRS) automatic protocolling of chest CT imaging requests. 322 387 consecutive historical imaging requests for chest CT between 2017 and 2022 were extracted from a radiology i...

Predicting postoperative prognosis in clear cell renal cell carcinoma using a multiphase CT-based deep learning model.

Abdominal radiology (New York)
BACKGROUND: Some clinicopathological risk stratification systems (CRSSs) such as the leibovich score have been used to predict the postoperative prognosis of patients with clear cell renal cell carcinoma (ccRCC), but there are no reliable noninvasive...

Deep Learning-Based Classification of Early-Stage Mycosis Fungoides and Benign Inflammatory Dermatoses on H&E-Stained Whole-Slide Images: A Retrospective, Proof-of-Concept Study.

The Journal of investigative dermatology
The diagnosis of early-stage mycosis fungoides (MF) is challenging owing to shared clinical and histopathological features with benign inflammatory dermatoses. Recent evidence has shown that deep learning (DL) can assist pathologists in cancer classi...

Using a Disentangled Neural Network to Objectively Assess the Outcomes of Midfacial Surgery in Syndromic Craniosynostosis.

Plastic and reconstructive surgery
BACKGROUND: Advancements in artificial intelligence and the development of shape models that quantify normal head shape and facial morphology provide frameworks by which the outcomes of craniofacial surgery can be compared. In this work, the authors ...

Robotic task specific training for upper limb neurorehabilitation: a mixed methods feasibility trial reporting achievable dose.

Disability and rehabilitation
PURPOSE: Robotic devices for upper-limb neurorehabilitation allow an increase in intensity of practice, often relying on video game-based training strategies with limited capacity to individualise training and integrate functional training. This stud...