AIMC Topic: Treatment Outcome
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Detection of pathologic complete response using deep neural network-based endoscopic evaluation in patients with esophageal cancer receiving neoadjuvant chemotherapy: a nationwide multicenter retrospective study from 46 Japanese esophageal centers.
Esophagus : official journal of the Japan Esophageal Society
Apr 28, 2025
BACKGROUND: Detecting pathological complete response (pCR) preoperatively facilitated a non-surgical approach after neoadjuvant chemotherapy (NAC). We previously developed a deep neural network-based endoscopic evaluation to determine pCR preoperativ...
Deep Learning
Treatment Outcome
Neoadjuvant Therapy
Predictive Value of Tests
Aged
Sensitivity and Specificity
Male
Middle Aged
Esophagoscopy
Pathologic Complete Response
Esophageal Neoplasms
Japan
Esophageal Squamous Cell Carcinoma
Chemotherapy, Adjuvant
Humans
Neural Networks, Computer
Retrospective Studies
Female
Predictive modeling of response to repetitive transcranial magnetic stimulation in treatment-resistant depression.
Translational psychiatry
Apr 27, 2025
Identifying predictors of treatment response to repetitive transcranial magnetic stimulation (rTMS) remain elusive in treatment-resistant depression (TRD). Leveraging electronic medical records (EMR), this retrospective cohort study applied supervise...
A pioneering artificial intelligence tool to predict treatment outcomes in ovarian cancer via diagnostic laparoscopy.
Scientific reports
Apr 25, 2025
Ovarian cancer is associated with high rates of patient mortality and morbidity. Laparoscopic assessment of tumor localization can be used for treatment planning in newly diagnosed high-grade serous ovarian carcinoma (HGSOC). While spread to multiple...
Predictive Model of Objective Response to Nivolumab Monotherapy for Advanced Renal Cell Carcinoma by Machine Learning Using Genetic and Clinical Data: The SNiP-RCC Study.
JCO clinical cancer informatics
Apr 25, 2025
PURPOSE: Anti-PD-1 antibodies are widely used for cancer treatment, including in advanced renal cell carcinoma (RCC). However, the therapeutic response varies among patients. This study aimed to predict tumor response to nivolumab anti-PD-1 antibody ...
Predicting outcomes following open abdominal aortic aneurysm repair using machine learning.
Scientific reports
Apr 24, 2025
Patients undergoing open surgical repair of abdominal aortic aneurysm (AAA) have a high risk of post-operative complications. However, there are no widely used tools to predict surgical risk in this population. We used machine learning (ML) technique...
Single Joint Hybrid Assistive Limb (HAL-SJ) robotic exoskeleton therapy in improving functional outcomes among workers with wrist fractures: Study protocol for a randomized controlled trial.
PloS one
Apr 24, 2025
INTRODUCTION: Robotic technologies have been developed for motor rehabilitation and such robots have shown favourable results when compared with equivalent doses of usual clinical therapy. Recently, robotic interventions have been suggested to be app...
Pancreas rejection: quieting the storm to preserve graft function.
Current opinion in organ transplantation
Apr 23, 2025
PURPOSE OF REVIEW: Allograft rejection remains enigmatic and elusive following pancreas transplantation. In the absence of early technical pancreas graft failure, pancreas allograft rejection is the major cause of death-censored pancreas graft loss b...
Comparison of machine learning models with conventional statistical methods for prediction of percutaneous coronary intervention outcomes: a systematic review and meta-analysis.
BMC cardiovascular disorders
Apr 23, 2025
INTRODUCTION: Percutaneous coronary intervention (PCI) has been the main treatment of coronary artery disease (CAD). In this review, we aimed to compare the performance of machine learning (ML) vs. logistic regression (LR) models in predicting differ...
Predicting responsiveness to a dialectical behaviour therapy skills training app for recurrent binge eating: A machine learning approach.
Behaviour research and therapy
Apr 22, 2025
OBJECTIVE: Smartphone applications (apps) show promise as an effective and scalable intervention modality for disordered eating, yet responsiveness varies considerably. The ability to predict user responses to app-based interventions is currently lim...
Comparing three neural networks to predict depression treatment outcomes in psychological therapies.
Behaviour research and therapy
Apr 22, 2025
OBJECTIVE: Artificial neural networks have been used in various fields to solve classification and prediction tasks. However, it is unclear if these may be adequate methods to predict psychological treatment outcomes. This study aimed to evaluate the...
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