AIMC Topic: Aged
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Machine learning models based on CT radiomics features for distinguishing benign and malignant vertebral compression fractures in patients with malignant tumors.
Acta radiologica (Stockholm, Sweden : 1987)
Oct 1, 2024
BACKGROUND: Radiomics has become an important tool for distinguishing benign and malignant vertebral compression fractures (VCFs). It is more clinically significant to concentrate on patients who have malignant tumors and differentiate between benign...
A machine learning approach in a monocentric cohort for predicting primary refractory disease in Diffuse Large B-cell lymphoma patients.
PloS one
Oct 1, 2024
INTRODUCTION: Primary refractory disease affects 30-40% of patients diagnosed with DLBCL and is a significant challenge in disease management due to its poor prognosis. Predicting refractory status could greatly inform treatment strategies, enabling ...
Deep Learning Classification of Ischemic Stroke Territory on Diffusion-Weighted MRI: Added Value of Augmenting the Input with Image Transformations.
Journal of imaging informatics in medicine
Sep 30, 2024
Our primary aim with this study was to build a patient-level classifier for stroke territory in DWI using AI to facilitate fast triage of stroke to a dedicated stroke center. A retrospective collection of DWI images of 271 and 122 consecutive acute i...
Machine learning model outperforms the ACS Risk Calculator in predicting non-home discharge following primary total knee arthroplasty.
Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA
Sep 30, 2024
PURPOSE: Despite the increase in outpatient total knee arthroplasty (TKA) procedures, many patients are still discharged to non-home locations following index surgery. The ability to accurately predict non-home discharge (NHD) following TKAs has the ...
Deep learning model for automated diagnosis of degenerative cervical spondylosis and altered spinal cord signal on MRI.
The spine journal : official journal of the North American Spine Society
Sep 30, 2024
BACKGROUND CONTEXT: A deep learning (DL) model for degenerative cervical spondylosis on MRI could enhance reporting consistency and efficiency, addressing a significant global health issue.
Prediction of Lesion-Based Treatment Response after Two Cycles of Lu-177 Prostate Specific Membrane Antigen Treatment in Metastatic Castration-Resistant Prostate Cancer Using Machine Learning.
Urologia internationalis
Sep 30, 2024
INTRODUCTION: Lutetium-177 (Lu-177) prostate-specific membrane antigen (PSMA) therapy is a radionuclide treatment that prolongs overall survival in metastatic castration-resistant prostate cancer (MCRPC). We aimed to predict lesion-based treatment re...
Glutamate Carboxypeptidase II
Lutetium
Prostatic Neoplasms, Castration-Resistant
Radioisotopes
Antigens, Surface
Gallium Radioisotopes
Retrospective Studies
Aged
Aged, 80 and over
Male
Middle Aged
Humans
Treatment Outcome
Machine Learning
Positron Emission Tomography Computed Tomography
Radiopharmaceuticals
Neoplasm Metastasis
Prognostic prediction of gastric cancer based on H&E findings and machine learning pathomics.
Molecular and cellular probes
Sep 30, 2024
AIM: In this research, we aimed to develop a model for the accurate prediction of gastric cancer based on H&E findings combined with machine learning pathomics.
Patient-Specific Myocardial Infarction Risk Thresholds From AI-Enabled Coronary Plaque Analysis.
Circulation. Cardiovascular imaging
Sep 30, 2024
BACKGROUND: Plaque quantification from coronary computed tomography angiography has emerged as a valuable predictor of cardiovascular risk. Deep learning can provide automated quantification of coronary plaque from computed tomography angiography. We...
Application of a deep-learning marker for morbidity and mortality prediction derived from retinal photographs: a cohort development and validation study.
The lancet. Healthy longevity
Sep 30, 2024
BACKGROUND: Biological ageing markers are useful to risk stratify morbidity and mortality more precisely than chronological age. In this study, we aimed to develop a novel deep-learning-based biological ageing marker (referred to as RetiPhenoAge here...
Retrospective Analysis of Radiofrequency Ablation in Patients with Small Solitary Hepatocellular Carcinoma: Survival Outcomes and Development of a Machine Learning Prognostic Model.
Current medical science
Sep 30, 2024
BACKGROUND AND OBJECTIVE: The effectiveness of radiofrequency ablation (RFA) in improving long-term survival outcomes for patients with a solitary hepatocellular carcinoma (HCC) measuring 5 cm or less remains uncertain. This study was designed to elu...
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