AIMC Topic: Treatment Outcome
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Mechanistic Learning for Predicting Survival Outcomes in Head and Neck Squamous Cell Carcinoma.
CPT: pharmacometrics & systems pharmacology
Dec 25, 2024
We employed a mechanistic learning approach, integrating on-treatment tumor kinetics (TK) modeling with various machine learning (ML) models to address the challenge of predicting post-progression survival (PPS)-the duration from the time of document...
Effect of artificial intelligence-based video-game system on dysphagia in patients with stroke: A randomized controlled trial.
Clinical nutrition (Edinburgh, Scotland)
Dec 25, 2024
BACKGROUND AND AIMS: Post-stroke dysphagia is highly prevalent and causes complication. While video games have demonstrated potential to increase patient engagement in rehabilitation, their efficacy in stroke patients with dysphagia remains unclear. ...
Radiomics and deep learning models for glioblastoma treatment outcome prediction based on tumor invasion modeling.
Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
Dec 25, 2024
PURPOSE: We investigate the feasibility of using a biophysically guided approach for delineating the Clinical Target Volume (CTV) in Glioblastoma Multiforme (GBM) by evaluating its impact on the treatment outcomes, specifically Overall Survival (OS) ...
Machine Learning Model for Risk Prediction of Prolonged Intensive Care Unit in Patients Receiving Intra-aortic Balloon Pump Therapy during Coronary Artery Bypass Graft Surgery.
Journal of cardiovascular translational research
Dec 24, 2024
This study aimed to construct machine learning models and predict prolonged intensive care units (ICU) stay in patients receiving perioperative intra-aortic balloon pump (IABP) therapy during cardiac surgery. 236 patients were divided into the normal...
Coronary Artery Bypass
Risk Factors
Intra-Aortic Balloon Pumping
Aged
Male
Decision Support Techniques
Middle Aged
Retrospective Studies
Risk Assessment
Intensive Care Units
Humans
Length of Stay
Female
Machine Learning
Time Factors
Reproducibility of Results
Treatment Outcome
Predictive Value of Tests
Predicting macular hole surgery outcomes: Integrating preoperative OCT features with supervised machine learning statistical models.
Indian journal of ophthalmology
Dec 24, 2024
PURPOSE: To evaluate various supervised machine learning (ML) statistical models to predict anatomical outcomes after macular hole (MH) surgery using preoperative optical coherence tomography (OCT) features.
Machine Learning-Driven Identification of Distinct Persistent Atrial Fibrillation Phenotypes: A Cluster Analysis of DECAAF II.
Journal of cardiovascular electrophysiology
Dec 23, 2024
INTRODUCTION: Catheter ablation of persistent atrial fibrillation yields sub-optimal success rates partly due to the considerable heterogeneity within the patient population. Identifying distinct patient phenotypes based on post-ablation prognosis co...
Integration of Graph Neural Networks and multi-omics analysis identify the predictive factor and key gene for immunotherapy response and prognosis of bladder cancer.
Journal of translational medicine
Dec 23, 2024
OBJECTIVE: The evaluation of the efficacy of immunotherapy is of great value for the clinical treatment of bladder cancer. Graph Neural Networks (GNNs), pathway analysis and multi-omics analysis have shown great potential in the field of cancer diagn...
Humans
Neural Networks, Computer
Prognosis
Reproducibility of Results
Tumor Microenvironment
Multiomics
Gene Expression Regulation, Neoplastic
Cell Proliferation
Treatment Outcome
Urinary Bladder Neoplasms
Cell Line, Tumor
Single-Cell Analysis
Computational Biology
Immunotherapy
Cell Movement
Apoptosis
Proteasome Endopeptidase Complex
Multi-branch CNNFormer: a novel framework for predicting prostate cancer response to hormonal therapy.
Biomedical engineering online
Dec 23, 2024
PURPOSE: This study aims to accurately predict the effects of hormonal therapy on prostate cancer (PC) lesions by integrating multi-modality magnetic resonance imaging (MRI) and the clinical marker prostate-specific antigen (PSA). It addresses the li...
Artificial Intelligence and Machine Learning Predicting Transarterial Chemoembolization Outcomes: A Systematic Review.
Digestive diseases and sciences
Dec 21, 2024
BACKGROUND: Major society guidelines recommend transarterial chemoembolization (TACE) as the standard of care for intermediate-stage hepatocellular carcinoma (HCC) patients. However, predicting treatment response remains challenging.
Assessing the prognostic impact of body composition phenotypes on surgical outcomes and survival in patients with spinal metastasis: a deep learning approach to preoperative CT analysis.
Journal of neurosurgery. Spine
Dec 20, 2024
OBJECTIVE: The prognostic significance of body composition phenotypes for survival in patients undergoing surgical intervention for spinal metastases has not yet been elucidated. This study aimed to elucidate the impact of body composition phenotypes...
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