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Principles for enhancing trust in artificial intelligence systems among medical imaging professionals in Ghana: A nationwide cross-sectional study.
Radiography (London, England : 1995)
Apr 13, 2025
INTRODUCTION: To realise the full potential of artificial intelligence (AI) systems in medical imaging, it is crucial to address challenges, such as cyberterrorism to foster trust and acceptance. This study aimed to determine the principles that enha...
Machine learning models for improving the diagnosing efficiency of skeletal class I and III in German orthodontic patients.
Scientific reports
Apr 13, 2025
The precise and efficient diagnosis of an individual's skeletal class is necessary in orthodontics to ensure correct and stable treatment planning. However, it is difficult to efficiently determine the true skeletal class due to several correlations ...
Deep learning enabled liquid-based cytology model for cervical precancer and cancer detection.
Nature communications
Apr 13, 2025
Deep learning (DL) enabled liquid-based cytology has potential for cervical cancer screening or triage. Here, we develop a DL model using whole cytology slides from 17,397 women and test it on 10,826 additional cases through a three-stage process. Th...
Development of a machine learning-based diagnostic model using hematological parameters to differentiate periductal mastitis from granulomatous lobular mastitis.
Science progress
Apr 13, 2025
ObjectiveNonpuerperal mastitis (NPM) is an inflammatory condition, including periductal mastitis (PDM) and granulomatous lobular mastitis (GLM). The clinical manifestations of PDM and GLM are highly similar, posing significant challenges in their dif...
Machine learning-based MRI radiomics to predict postoperative complications following peripheral nerve sheath tumour excision.
The Journal of hand surgery, European volume
Apr 12, 2025
This study sought to establish and validate a machine learning-based multi-sequence MRI radiomics model for predicting postoperative complications in patients with peripheral nerve sheath tumours. We conducted a retrospective analysis of 303 patients...
MRI radiomics combined with delta-radiomics model for predicting pathological complete response in locally advanced rectal cancer patients after neoadjuvant chemoradiotherapy: A multi-institutional study.
Applied radiation and isotopes : including data, instrumentation and methods for use in agriculture, industry and medicine
Apr 12, 2025
PURPOSE: To construct and validate a magnetic resonance imaging (MRI) radiomics combined with delta-radiomics and clinical information (C) model for predicting pathological complete response (pCR) in patients with locally advanced rectal cancer (LARC...
A diagnosis and prediction algorithm for juvenile myoclonic epilepsy based on clinical and quantitative EEG features.
Seizure
Apr 12, 2025
OBJECTIVE: To develop an objective ensemble machine learning model combining clinical features and quantitative EEG metrics (phase locking value [PLV] and multiscale sample entropy [MSE]) to support accurate diagnosis of juvenile myoclonic epilepsy (...
Automatic video analysis of countermovement jump performance using a single uncalibrated camera.
Journal of biomechanics
Apr 12, 2025
The countermovement jump (CMJ) assessment is widely employed for monitoring sports performance, traditionally relying on heavy and expensive force plates to extract performance variables like jump height and peak force. Inertial measurement unit (IMU...
Estimating gait parameters from sEMG signals using machine learning techniques under different power capacity of muscle.
Scientific reports
Apr 12, 2025
The gait analysis has been applied in many fields, such as the assessment of falling, force evaluation in sports, and gait disorder detection for neuromuscular diseases. Its main recording techniques include video cameras and wearable sensors. Howeve...
Machine learning-based differentiation of schizophrenia and bipolar disorder using multiscale fuzzy entropy and relative power from resting-state EEG.
Translational psychiatry
Apr 12, 2025
Schizophrenia (SZ) and bipolar disorder (BD) pose diagnostic challenges due to overlapping clinical symptoms and genetic factors, often resulting in misdiagnosis and suboptimal treatment outcomes. This study aimed to identify EEG-based biomarkers tha...
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