AIMC Topic: Aged

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Identification of patient demographic, clinical, and SARS-CoV-2 genomic factors associated with severe COVID-19 using supervised machine learning: a retrospective multicenter study.

BMC infectious diseases
BACKGROUND: Drivers of COVID-19 severity are multifactorial and include multidimensional and potentially interacting factors encompassing viral determinants and host-related factors (i.e., demographics, pre-existing conditions and/or genetics), thus ...

OCT-based diagnosis of glaucoma and glaucoma stages using explainable machine learning.

Scientific reports
Glaucoma poses a growing health challenge projected to escalate in the coming decades. However, current automated diagnostic approaches on Glaucoma diagnosis solely rely on black-box deep learning models, lacking explainability and trustworthiness. T...

User and Developer Views on Using AI Technologies to Facilitate the Early Detection of Skin Cancers in Primary Care Settings: Qualitative Semistructured Interview Study.

JMIR cancer
BACKGROUND: Skin cancers, including melanoma and keratinocyte cancers, are among the most common cancers worldwide, and their incidence is rising in most populations. Earlier detection of skin cancer leads to better outcomes for patients. Artificial ...

A Deep Learning Tool for Minimum Joint Space Width Calculation on Antero-posterior Knee Radiographs.

The Journal of arthroplasty
BACKGROUND: Minimum joint space width (mJSW) is an important continuous quantitative metric of osteoarthritis progression in the knee. The purpose of this study was to develop an automated measurement algorithm for mJSW in the medial and lateral comp...

Development of a Deep Learning Model for Automating Implant Position in Total Hip Arthroplasty.

The Journal of arthroplasty
BACKGROUND: Novel methods for annotating antero-posterior pelvis radiographs and fluoroscopic images with deep-learning models have recently been developed. However, their clinical use has been limited. Therefore, the purpose of this study was to dev...

Prediction of the Serial Alignment Change after Opening-Wedge High Tibial Osteotomy Based on Coronal Plane Alignment of the Knee Using Machine Learning Algorithm.

The journal of knee surgery
Categorization of alignment into phenotypes can be useful for predicting and analyzing postoperative alignment changes after opening-wedge high tibial osteotomy (OWHTO). The purposes of this study were to (1) develop a machine learning model for the ...

Identifying Primary Sites of Spinal Metastases: Expert-Derived Features vs. ResNet50 Model Using Nonenhanced MRI.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: The spinal column is a frequent site for metastases, affecting over 30% of solid tumor patients. Identifying the primary tumor is essential for guiding clinical decisions but often requires resource-intensive diagnostics.

An Artificial Intelligence Model Using Diffusion Basis Spectrum Imaging Metrics Accurately Predicts Clinically Significant Prostate Cancer.

The Journal of urology
PURPOSE: Conventional prostate magnetic resonance imaging has limited accuracy for clinically significant prostate cancer (csPCa). We performed diffusion basis spectrum imaging (DBSI) before biopsy and applied artificial intelligence models to these ...

A novel clinical investigation using deep learning and human-in-the-loop approach in orbital volume measurement.

Journal of cranio-maxillo-facial surgery : official publication of the European Association for Cranio-Maxillo-Facial Surgery
Orbital volume assessment is crucial for surgical planning. Traditional methods lack efficiency and accuracy. Recent studies explore AI-driven techniques, but research on their clinical effectiveness is limited. This study included 349 patients aged ...