AIMC Topic: Treatment Outcome
Clear Filters Showing 401 to 410 of 3204 articles
Approved AI-based fluid monitoring to identify morphological and functional treatment outcomes in neovascular age-related macular degeneration in real-world routine.
The British journal of ophthalmology
Jun 20, 2024
AIM: To predict antivascular endothelial growth factor (VEGF) treatment requirements, visual acuity and morphological outcomes in neovascular age-related macular degeneration (nAMD) using fluid quantification by artificial intelligence (AI) in a real...
Female
Aged
Aged, 80 and over
Male
Angiogenesis Inhibitors
Humans
Artificial Intelligence
Retrospective Studies
Vascular Endothelial Growth Factor A
Intravitreal Injections
Ranibizumab
Wet Macular Degeneration
Subretinal Fluid
Treatment Outcome
Follow-Up Studies
Visual Acuity
Tomography, Optical Coherence
Application of machine learning in the analysis of multiparametric MRI data for the differentiation of treatment responses in breast cancer: retrospective study.
European journal of cancer prevention : the official journal of the European Cancer Prevention Organisation (ECP)
Jun 19, 2024
OBJECTIVE: The objective of this study is to develop and validate a multiparametric MRI model employing machine learning to predict the effectiveness of treatment and the stage of breast cancer.
Machine Learning to Predict Prostate Artery Embolization Outcomes.
Cardiovascular and interventional radiology
Jun 19, 2024
PURPOSE: This study leverages pre-procedural data and machine learning (ML) techniques to predict outcomes at one year following prostate artery embolization (PAE).
Individual Predictors of Response to A Behavioral Activation-Based Digital Smoking Cessation Intervention: A Machine Learning Approach.
Substance use & misuse
Jun 19, 2024
Depression is prevalent among individuals who smoke cigarettes and increases risk for relapse. A previous clinical trial suggests that Goal2Quit, a behavioral activation-based smoking cessation mobile app, effectively increases smoking abstinence an...
A machine learning radiomics based on enhanced computed tomography to predict neoadjuvant immunotherapy for resectable esophageal squamous cell carcinoma.
Frontiers in immunology
Jun 14, 2024
BACKGROUND: Patients with resectable esophageal squamous cell carcinoma (ESCC) receiving neoadjuvant immunotherapy (NIT) display variable treatment responses. The purpose of this study is to establish and validate a radiomics based on enhanced comput...
Evaluation of machine learning approach for surgical results of Ahmed valve implantation in patients with glaucoma.
BMC ophthalmology
Jun 11, 2024
BACKGROUND: Ahmed valve implantation demonstrated an increasing proportion in glaucoma surgery, but predicting the successful maintenance of target intraocular pressure remains a challenging task. This study aimed to evaluate the performance of machi...
Machine Learning in Electroconvulsive Therapy: A Systematic Review.
The journal of ECT
Jun 10, 2024
Despite years of research, we are still not able to reliably predict who might benefit from electroconvulsive therapy (ECT) treatment. As we exhaust what is possible using traditional statistical analysis, ECT remains a good candidate for machine lea...
Predicting the Efficacy of Repeated Shockwave Lithotripsy for Treating Patients with Upper Urinary Tract Calculi Using an Artificial Neural Network Model.
Urology journal
Jun 9, 2024
PURPOSE: To establish a prediction model for repeated shockwave lithotripsy (SWL) efficacy to help choose an appropriate treatment plan for patients with a single failed lithotripsy, reducing their treatment burden.
Time-Series MR Images Identifying Complete Response to Neoadjuvant Chemotherapy in Breast Cancer Using a Deep Learning Approach.
Journal of magnetic resonance imaging : JMRI
Jun 8, 2024
BACKGROUND: Pathological complete response (pCR) is an essential criterion for adjusting follow-up treatment plans for patients with breast cancer (BC). The value of the visual geometry group and long short-term memory (VGG-LSTM) network using time-s...
Exoskeleton rehabilitation robot training for balance and lower limb function in sub-acute stroke patients: a pilot, randomized controlled trial.
Journal of neuroengineering and rehabilitation
Jun 8, 2024
PURPOSE: This pilot study aimed to investigate the effects of REX exoskeleton rehabilitation robot training on the balance and lower limb function in patients with sub-acute stroke.
Stay Ahead of Medical AI
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.
Subscribe NowPopular Topics
- Machine Learning 32065
- Neural Networks, Computer 30249
- Algorithms 27433
- Deep Learning 26935
- Artificial Intelligence 24866
- Robotics 13394
- Image Processing, Computer-Assisted 9746
- Retrospective Studies 9358
- Magnetic Resonance Imaging 6353
- Reproducibility of Results 5671
- Tomography, X-Ray Computed 4869
- Support Vector Machine 4774
- Computational Biology 4337
- Brain 4132
- Computer Simulation 3936
Recent Journals
- Scientific reports 6855
- Sensors (Basel, Switzerland) 4794
- PloS one 4219
- Neural networks : the official journal of the International Neural Network Society 3026
- Computational intelligence and neuroscience 1931
- Computers in biology and medicine 1920
- Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference 1686
- Studies in health technology and informatics 1378
- IEEE journal of biomedical and health informatics 1178
- Journal of chemical information and modeling 1070
- Nature communications 1054
- Computer methods and programs in biomedicine 883
- Bioinformatics (Oxford, England) 877
- Journal of medical Internet research 867
- IEEE transactions on neural networks and learning systems 854