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Drug knowledge discovery via multi-task learning and pre-trained models
BackgroundDrug repurposing is to find new indications of approved drugs, which is essential for investigating new uses for approved or...
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Mental fatigue impairs strength endurance performance in trained individuals
PurposeEvidence of mental fatigue (MF) effects on dynamic strength performance and psychological responses is scarce and controversial. Thus, we...
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Task-aware asynchronous multi-task model with class incremental contrastive learning for surgical scene understanding
PurposeSurgery scene understanding with tool-tissue interaction recognition and automatic report generation can play an important role in...
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Task Shifting and Task Sharing to Strengthen the Surgical Workforce in Sub-Saharan Africa: A Systematic Review of the Existing Literature
BackgroundA major constraint to surgical care delivery in low-resource settings is inadequate workforce availability. Surgical task shifting...
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Quantifying impairment and disease severity using AI models trained on healthy subjects
Automatic assessment of impairment and disease severity is a key challenge in data-driven medicine. We propose a framework to address this challenge,...
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Improving MR image quality with a multi-task model, using convolutional losses
PurposeDuring the acquisition of MRI data, patient-, sequence-, or hardware-related factors can introduce artefacts that degrade image quality. Four...
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Biceps brachii elastography in well-trained men post eccentric exercise-induced muscle damage
PurposeRecent advancements in elastography techniques, specifically supersonic shearwave elastography (SWE), have enabled non-invasive assessment of...
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Independently Trained Multi-Scale Registration Network Based on Image Pyramid
Image registration is a fundamental task in various applications of medical image analysis and plays a crucial role in auxiliary diagnosis,...
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Task Control in the Affordance Task as the Underlying Mechanism for the Imbalance Between the Goal-Directed and Habit Formation Systems in Obsessive–Compulsive Disorder
Background and ObjectivesThe habit formation model of obsessive–compulsive disorder (OCD) suggests that overreliance on stimulus-driven behaviors...
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A comparative study of pre-trained language models for named entity recognition in clinical trial eligibility criteria from multiple corpora
BackgroundClinical trial protocols are the foundation for advancing medical sciences, however, the extraction of accurate and meaningful information...
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Task-based assessment of resolution properties of CT images with a new index using deep convolutional neural network
In this study, we propose a method for obtaining a new index to evaluate the resolution properties of computed tomography (CT) images in a task-based...
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Multiple Kernel Synthesis of Head CT Using a Task-Based Loss Function
In CT imaging of the head, multiple image series are routinely reconstructed with different kernels and slice thicknesses. Reviewing the redundant...
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CheSS: Chest X-Ray Pre-trained Model via Self-supervised Contrastive Learning
Training deep learning models on medical images heavily depends on experts’ expensive and laborious manual labels. In addition, these images, labels,...
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Evaluating the performance of Generative Pre-trained Transformer-4 (GPT-4) in standardizing radiology reports
ObjectiveRadiology reporting is an essential component of clinical diagnosis and decision-making. With the advent of advanced artificial intelligence...
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Multi-task learning-based histologic subtype classification of non-small cell lung cancer
PurposeIn clinical applications, accurate histologic subtype classification of lung cancer is important for determining appropriate treatment plans....
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Use of Buffers in Specific Contexts: Highly Trained Female Athletes, Extreme Environments and Combined Buffering Agents—A Narrative Review
This narrative review evaluated the evidence for buffering agents (sodium bicarbonate, sodium citrate and beta-alanine), with specific consideration...
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Human Monkeypox Classification from Skin Lesion Images with Deep Pre-trained Network using Mobile Application
Recently, human monkeypox outbreaks have been reported in many countries. According to the reports and studies, quick determination and isolation of...
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Refining the study of decision-making in animals: differential effects of d-amphetamine and haloperidol in a novel touchscreen-automated Rearing-Effort Discounting (RED) task and the Fixed-Ratio Effort Discounting (FRED) task
Effort-based decision-making is impaired in multiple psychopathologies leading to significant impacts on the daily life of patients. Preclinical...
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The development of task-specific metrics for grading the robotic gastrojejunostomy in robotic pancreaticoduodenectomy
BackgroundMinimally invasive surgery affords the opportunity for video review. Procedures are unique and global assessments may not be helpful in...
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Task model-specific operator skill assessment in routine fetal ultrasound scanning
PurposeFor highly operator-dependent ultrasound scanning, skill assessment approaches evaluate operator competence given available data, such as...
