AIMC Topic: Aged
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Sex-Specific Imaging Biomarkers for Parkinson's Disease Diagnosis: A Machine Learning Analysis.
Journal of imaging informatics in medicine
Sep 10, 2024
This study aimed to identify sex-specific imaging biomarkers for Parkinson's disease (PD) based on multiple MRI morphological features by using machine learning methods. Participants were categorized into female and male subgroups, and various struct...
Contrast-Enhanced Computed Tomography-Based Machine Learning Radiomics Predicts IDH1 Expression and Clinical Prognosis in Head and Neck Squamous Cell Carcinoma.
Academic radiology
Sep 10, 2024
RATIONALE AND OBJECTIVES: Isocitrate dehydrogenase 1 (IDH1) is a potential therapeutic target across various tumor types. Here, we aimed to devise a radiomic model capable of predicting the IDH1 expression levels in patients with head and neck squamo...
Radiomics Analysis of Intratumoral and Various Peritumoral Regions From Automated Breast Volume Scanning for Accurate Ki-67 Prediction in Breast Cancer Using Machine Learning.
Academic radiology
Sep 10, 2024
RATIONALE AND OBJECTIVES: Current radiomics research primarily focuses on intratumoral regions and fixed peritumoral areas, lacking optimization for accurate Ki-67 prediction. This study aimed to develop machine learning (ML) models to analyze radiom...
Applying deep learning-based ensemble model to [F]-FDG-PET-radiomic features for differentiating benign from malignant parotid gland diseases.
Japanese journal of radiology
Sep 10, 2024
OBJECTIVES: To develop and identify machine learning (ML) models using pretreatment 2-deoxy-2-[F]fluoro-D-glucose ([F]-FDG)-positron emission tomography (PET)-based radiomic features to differentiate benign from malignant parotid gland diseases (PGDs...
MYC Rearrangement Prediction From LYSA Whole Slide Images in Large B-Cell Lymphoma: A Multicentric Validation of Self-supervised Deep Learning Models.
Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc
Sep 10, 2024
Large B-cell lymphoma (LBCL) is a heterogeneous lymphoid malignancy in which MYC gene rearrangement (MYC-R) is associated with a poor prognosis, prompting the recommendation for more intensive treatment. MYC-R detection relies on fluorescence in situ...
Preoperative treatment response prediction for pancreatic cancer by multiple microRNAs in plasma exosomes: Optimization using machine learning and network analysis.
Pancreatology : official journal of the International Association of Pancreatology (IAP) ... [et al.]
Sep 10, 2024
BACKGROUND/OBJECTIVES: MicroRNAs (miRNAs) are involved in chemosensitivity through their biological activities in various malignancies, including pancreatic cancer (PC). However, single-miRNA models offer limited predictability of treatment response....
Effect of machine learning models on clinician prediction of postoperative complications: the Perioperative ORACLE randomised clinical trial.
British journal of anaesthesia
Sep 10, 2024
BACKGROUND: Anaesthesiologists might be able to mitigate risk if they know which patients are at greatest risk for postoperative complications. This trial examined the impact of machine learning models on clinician risk assessment.
Deep learning Radiomics Based on Two-Dimensional Ultrasound for Predicting the Efficacy of Neoadjuvant Chemotherapy in Breast Cancer.
Ultrasonic imaging
Sep 10, 2024
We investigate the predictive value of a comprehensive model based on preoperative ultrasound radiomics, deep learning, and clinical features for pathological complete response (pCR) after neoadjuvant chemotherapy (NAC) for the breast cancer. We enro...
Integrating chemokines and machine learning algorithms for diagnosis and bleeding assessment in primary immune thrombocytopenia: A prospective cohort study.
British journal of haematology
Sep 10, 2024
Primary immune thrombocytopenia (ITP) is an autoimmune bleeding disorder, and chemokines have been shown to be dysregulated in autoimmune disorders. We conducted a prospective analysis to identify potential chemokines that could enhance the diagnosti...
Aging-related biomarkers for the diagnosis of Parkinson's disease based on bioinformatics analysis and machine learning.
Aging
Sep 10, 2024
Parkinson's disease (PD) is a multifactorial disease that lacks reliable biomarkers for its diagnosis. It is now clear that aging is the greatest risk factor for developing PD. Therefore, it is necessary to identify novel biomarkers associated with a...
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