AIMC Topic: Treatment Outcome
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Common genetic variants do not impact clinical prediction of methotrexate treatment outcomes in early rheumatoid arthritis.
Journal of internal medicine
Apr 6, 2025
BACKGROUND: Methotrexate (MTX) is the mainstay initial treatment of rheumatoid arthritis (RA), but individual response varies and remains difficult to predict. The role of genetics remains unclear, but studies suggest its importance.
Interim results of exoskeletal wearable robot for gait recovery in subacute stroke patients.
Scientific reports
Apr 5, 2025
Exoskeletons have been proposed for potential clinical use to improve ambulatory function in patients with stroke. The aim of an interim analysis of an international, multicenter, randomized, controlled trial was to investigate the short-term effect ...
Using Real-World Data for Machine-Learning Algorithms to Predict the Treatment Response in Advanced Melanoma: A Pilot Study for Personalizing Cancer Care.
JCO clinical cancer informatics
Apr 4, 2025
PURPOSE: The use of real-world data (RWD) in oncology is becoming increasingly important for clinical decision making and tailoring treatment. Despite the significant success of targeted therapy and immunotherapy in advanced melanoma, substantial var...
AI-driven analyzes of open-ended responses to assess outcomes of internet-based cognitive behavioral therapy (ICBT) in adolescents with anxiety and depression comorbidity.
Journal of affective disorders
Apr 3, 2025
OBJECTIVE: Although patients prefer describing their problems using words, mental health interventions are commonly evaluated using rating scales. Fortunately, recent advances in natural language processing (i.e., AI-methods) yield new opportunities ...
Early prediction of neoadjuvant therapy response in breast cancer using MRI-based neural networks: data from the ACRIN 6698 trial and a prospective Chinese cohort.
Breast cancer research : BCR
Apr 3, 2025
BACKGROUND: Early prediction of treatment response to neoadjuvant therapy (NAT) in breast cancer patients can facilitate timely adjustment of treatment regimens. We aimed to develop and validate a MRI-based enhanced self-attention network (MESN) for ...
Urinary biomarkers of kidney transplant rejection.
Current opinion in organ transplantation
Apr 2, 2025
PURPOSE OF REVIEW: Despite the introduction of many new immunosuppressive medications, allograft rejection remains a significant complication in transplantation. The use of "liquid biopsy" to evaluate allograft function and detect early rejection has...
Metabolomic machine learning-based model predicts efficacy of chemoimmunotherapy for advanced lung squamous cell carcinoma.
Frontiers in immunology
Apr 2, 2025
BACKGROUND: Unlike lung adenocarcinoma, patients with advanced squamous carcinoma exhibit a low proportion of driver gene positivity, with fewer effective treatment strategies available. Chemoimmunotherapy has now become the standard first-line treat...
Machine Learning-Guided Fluid Resuscitation for Acute Pancreatitis Improves Outcomes.
Clinical and translational gastroenterology
Apr 1, 2025
INTRODUCTION: Ariel Dynamic Acute Pancreatitis Tracker (ADAPT) is an artificial intelligence tool using mathematical algorithms to predict severity and manage fluid resuscitation needs based on the physiologic parameters of individual patients. Our a...
Effectiveness of a community intervention program on healthy lifestyles (PREDICOL) among adults with prediabetes in two Latin American cities: A quasi-experimental study.
Primary care diabetes
Mar 29, 2025
PURPOSE: This study aimed to measure the impact of a community-based lifestyle modification intervention program on the Health-Related Quality of Life (HRQoL) of adults with prediabetes in two Latin American cities.
F-FDG PET radiomics score construction by automatic machine learning for treatment response prediction in elderly patients with diffuse large B-cell lymphoma: a multicenter study.
Journal of cancer research and clinical oncology
Mar 28, 2025
PURPOSE: To explore the development and validation of automated machine learning (AutoML) models for F-FDG PET imaging-based radiomics signatures to predict treatment response in elderly patients with diffuse large B-cell lymphoma (DLBCL).
Lymphoma, Large B-Cell, Diffuse
Male
Middle Aged
Antineoplastic Combined Chemotherapy Protocols
Treatment Outcome
Female
Aged
Humans
Radiopharmaceuticals
Aged, 80 and over
Prednisone
Radiomics
Machine Learning
Rituximab
Positron-Emission Tomography
Prognosis
Vincristine
Cyclophosphamide
Retrospective Studies
Fluorodeoxyglucose F18
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