AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Treatment Outcome

Showing 11 to 20 of 3067 articles

Clear Filters

Optimizing Treatment: The Role of Pharmacology, Genomics, and AI in Improving Patient Outcomes.

Drug development research
Recent advances in pharmacology are revolutionizing drug discovery and treatment strategies through personalized medicine, pharmacogenomics, and artificial intelligence (AI). The objective of the present study is to review the role of personalized me...

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
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...

Artificial intelligence in liver cancer surgery: Predicting success before the first incision.

World journal of gastroenterology
Advancements in machine learning have revolutionized preoperative risk assessment. In this article, we comment on the article by Huang , which presents a recent multicenter cohort study demonstrated that machine learning algorithms effectively strati...

Development and validation a radiomics combined clinical model predicts treatment response for esophageal squamous cell carcinoma patients.

BMC gastroenterology
PURPOSE: This study is aimed to develop and validate a machine learning model, which combined radiomics and clinical characteristics to predicting the definitive chemoradiotherapy (dCRT) treatment response in esophageal squamous cell carcinoma (ESCC)...

Predictive modeling of response to repetitive transcranial magnetic stimulation in treatment-resistant depression.

Translational psychiatry
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...

Predicting Weight Loss Success After Gastric Sleeve Surgery: A Machine Learning-Based Approach.

Nutrients
BACKGROUND/OBJECTIVES: Obesity is a global health issue, and in this context, bariatric surgery is considered the most effective treatment for severe cases. However, postoperative outcomes vary widely among individuals, driving the development of too...

A pioneering artificial intelligence tool to predict treatment outcomes in ovarian cancer via diagnostic laparoscopy.

Scientific reports
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
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
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...

Effects of exoskeleton rehabilitation robot training on neuroplasticity and lower limb motor function in patients with stroke.

BMC neurology
BACKGROUND: Lower limb exoskeleton rehabilitation robot is a new technology to improve the lower limb motor function of stroke patients. Recovery of motor function after stroke is closely related to neuroplasticity in the motor cortex and associated ...