AIMC Topic: Adult

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MRI-based automated multitask deep learning system to evaluate supraspinatus tendon injuries.

European radiology
OBJECTIVE: To establish an automated, multitask, MRI-based deep learning system for the detailed evaluation of supraspinatus tendon (SST) injuries.

Feasibility and limitations of deep learning-based coronary calcium scoring in PET-CT: a comparison with coronary calcium score CT.

European radiology
OBJECTIVE: This study aimed to determine the feasibility and limitations of deep learning-based coronary calcium scoring using positron emission tomography-computed tomography (PET-CT) in comparison with coronary calcium scoring using ECG-gated non-c...

Arthroscopic Bone Grafting and Robot-assisted Fixation for Scaphoid Nonunion.

Orthopaedic surgery
OBJECTIVES: Scaphoid nonunion remains a challenging problem to manage with no general consensus on its treatment recommendations. We propose a novel minimally invasive (MIS) technique of arthroscopic bone grafting (ABG) with robot-assisted fixation f...

Glioblastoma and Solitary Brain Metastasis: Differentiation by Integrating Demographic-MRI and Deep-Learning Radiomics Signatures.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: Studies have shown that deep-learning radiomics (DLR) could help differentiate glioblastoma (GBM) from solitary brain metastasis (SBM), but whether integrating demographic-MRI and DLR features can more accurately distinguish GBM from SBM ...

AI Hyperrealism: Why AI Faces Are Perceived as More Real Than Human Ones.

Psychological science
Recent evidence shows that AI-generated faces are now indistinguishable from human faces. However, algorithms are trained disproportionately on White faces, and thus White AI faces may appear especially realistic. In Experiment 1 ( = 124 adults), alo...

Effect of multimodal diagnostic approach using deep learning-based automated detection algorithm for active pulmonary tuberculosis.

Scientific reports
In this study, we developed a model to predict culture test results for pulmonary tuberculosis (PTB) with a customized multimodal approach and evaluated its performance in different clinical settings. Moreover, we investigated potential performance i...

Automated Segmentation and Classification of Knee Synovitis Based on MRI Using Deep Learning.

Academic radiology
OBJECTIVES: To develop a deep learning (DL) model for segmentation of the suprapatellar capsule (SC) and infrapatellar fat pad (IPFP) based on sagittal proton density-weighted images and to distinguish between three common types of knee synovitis.

Machine learning vs. traditional regression analysis for fluid overload prediction in the ICU.

Scientific reports
Fluid overload, while common in the ICU and associated with serious sequelae, is hard to predict and may be influenced by ICU medication use. Machine learning (ML) approaches may offer advantages over traditional regression techniques to predict it. ...

Predicting incident cardiovascular disease among African-American adults: A deep learning approach to evaluate social determinants of health in the Jackson heart study.

PloS one
The present study sought to leverage machine learning approaches to determine whether social determinants of health improve prediction of incident cardiovascular disease (CVD). Participants in the Jackson Heart study with no history of CVD at baselin...