AIMC Topic: Machine Learning
Clear Filters Showing 641 to 650 of 32555 articles
Advanced finite segmentation model with hybrid classifier learning for high-precision brain tumor delineation in PET imaging.
Scientific reports
Jul 15, 2025
Brain tumor segmentation plays a crucial role in clinical diagnostics and treatment planning, yet accurate and efficient segmentation remains a significant challenge due to complex tumor structures and variations in imaging modalities. Multi-feature ...
Developing angiogenesis-related prognostic biomarkers and therapeutic strategies in bladder cancer using deep learning and machine learning.
Scientific reports
Jul 15, 2025
Bladder cancer (BLCA) is a prevalent urological malignancy that exhibits a high degree of tumor heterogeneity and morbidity. Tumor angiogenesis, a vital hallmark of cancer, greatly influences the tumor microenvironment (TME). The emergence of anti-an...
Objective monitoring of motor symptom severity and their progression in Parkinson's disease using a digital gait device.
Scientific reports
Jul 15, 2025
Digital technologies for monitoring motor symptoms of Parkinson's Disease (PD) underwent a strong evolution during the past years. Although it has been shown for several devices that derived digital gait features can reliably discriminate between hea...
Developing a machine-learning model to enable treatment selection for neoadjuvant chemotherapy for esophageal cancer.
Scientific reports
Jul 15, 2025
Although neoadjuvant chemotherapy with docetaxel + cisplatin + 5-fluorouracil (CF) has been the standard treatment for stage II and III esophageal cancers, it is associated with severe adverse events caused by docetaxel. Consequently, this study aime...
Machine learning-enabled estimation of cardiac output from peripheral waveforms is independent of blood pressure measurement location in an in silico population.
Scientific reports
Jul 15, 2025
Monitoring of cardiac output (CO) is a mainstay of hemodynamic management in the acutely or critically ill patient. Invasive determination of CO using thermodilution, albeit regarded as the gold standard, is cumbersome and bears risks inherent to cat...
Evaluating cognitive decline detection in aging populations with single-channel EEG features based on two studies and meta-analysis.
Scientific reports
Jul 15, 2025
Timely detection of cognitive decline is paramount for effective intervention, prompting researchers to leverage EEG pattern analysis, focusing particularly on cognitive load, to establish reliable markers for early detection and intervention. This c...
Color Dynamics, Pigments and Antioxidant Capacity in Pouteria sapota Puree During Frozen Storage: A Correlation Study Using CIELAB Color Space and Machine Learning Models.
Plant foods for human nutrition (Dordrecht, Netherlands)
Jul 15, 2025
The accurate prediction of bioactive compounds and antioxidant activity in food matrices is critical for optimizing nutritional quality and industrial applications. This study compares the performance of multiple linear regression (MLR) and artificia...
NeXtMD: a new generation of machine learning and deep learning stacked hybrid framework for accurate identification of anti-inflammatory peptides.
BMC biology
Jul 15, 2025
BACKGROUND: Accurate identification of anti-inflammatory peptides (AIPs) is crucial for drug development and inflammatory disease treatment. However, the short length and limited informational content of peptide sequences make precise computational r...
Predicting patient risk of leaving without being seen using machine learning: a retrospective study in a single overcrowded emergency department.
BMC emergency medicine
Jul 15, 2025
Emergency department (ED) overcrowding has become a critical issue in hospital management, leading to increased patient wait times and higher rates of individuals leaving without being seen (LWBS). This study aims to identify key factors influencing ...
Machine learning survival models for Non-alcoholic fatty liver disease based on a health checkup cohort.
BMC gastroenterology
Jul 15, 2025
OBJECTIVES: This study aimed to develop an accurate prediction model for the risk of Non-alcoholic fatty liver disease (NAFLD) using the random survival forests (RSF), and to investigate the distribution of NAFLD risk with time.
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 32544
- Neural Networks, Computer 30502
- Algorithms 27746
- Deep Learning 27302
- Artificial Intelligence 25227
- Robotics 13430
- Image Processing, Computer-Assisted 9890
- Retrospective Studies 9537
- Magnetic Resonance Imaging 6484
- Reproducibility of Results 5746
- Tomography, X-Ray Computed 4963
- Support Vector Machine 4812
- Computational Biology 4397
- Brain 4188
- Computer Simulation 3963
Recent Journals
- Scientific reports 7013
- Sensors (Basel, Switzerland) 4794
- PloS one 4326
- Neural networks : the official journal of the International Neural Network Society 3035
- Computers in biology and medicine 2040
- Computational intelligence and neuroscience 1931
- 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 1395
- IEEE journal of biomedical and health informatics 1197
- Journal of chemical information and modeling 1088
- Nature communications 1072
- Computer methods and programs in biomedicine 895
- Journal of medical Internet research 880
- Bioinformatics (Oxford, England) 880
- IEEE transactions on neural networks and learning systems 859