A5086609415- AI-based Problem Solving and Planning
- Semantic Web and Ontologies
- Biomedical Text Mining and Ontologies
- Data Mining Algorithms and Applications
- Gene expression and cancer classification
- Logic, Reasoning, and Knowledge
- Rough Sets and Fuzzy Logic
- Artificial Intelligence in Healthcare
- Topic Modeling
- Machine Learning and Data Classification
- Cognitive Science and Mapping
- Machine Learning in Healthcare
- Advanced Text Analysis Techniques
- AI in cancer detection
- Explainable Artificial Intelligence (XAI)
- Bioinformatics and Genomic Networks
- Bayesian Modeling and Causal Inference
- Intelligent Tutoring Systems and Adaptive Learning
- Big Data and Business Intelligence
- Risk and Safety Analysis
- Emotion and Mood Recognition
- Heart Rate Variability and Autonomic Control
- Natural Language Processing Techniques
- Multi-Criteria Decision Making
- Machine Learning in Bioinformatics
State University of New York at Oswego
2014-2024
University of Connecticut
2022-2024
Southern Utah University
2016-2024
The University of Texas at Dallas
2024
Fundação Getulio Vargas
2023
Texas A&M University – Corpus Christi
2022
State Key Laboratory of Cryptology
2022
University of Central Florida
2022
University of Massachusetts Amherst
2022
North Dakota State University
2022
Physiological sensor analytics is becoming an important tool to monitor health as the availability of sensor-enabled portable, wearable, and implantable devices becomes ubiquitous in growing Internet Things (IoT). multi-sensor studies have been conducted previously detect stress. In this study, we focus on ECG monitoring that can now be performed with minimally invasive wearable patches sensors, develop efficient robust mechanism for accurate stress identification. A unique aspect our...
This commentary summarizes case-based reasoning research applied in the medical domain. In this term ‘medical’ is used an all-encompassing manner. It comprises all aspects of health, for example, from diagnosis to nutrition planning. article provides references researchers field, systems, workshops, and landmark publications.
Integrative multi-feature fusion analysis on biomedical data has gained much attention recently. In breast cancer, existing studies have demonstrated that combining genomic mRNA and DNA methylation can better stratify cancer patients with distinct prognosis than using single signature. However, those methods are simply these gene features in series ignored the correlations between separate omics dimensions over time.In present study, we propose an adaptive multi-task learning method, which...
The authors randomly selected 400 physicians from a population of 1,545 practicing providing follow-up care to patients who received bone marrow or blood stem cell transplants at the Fred Hutchinson Cancer Research Center determine interest in receiving Internet-based transplant information. In two-factor completely randomized factorial design, were assigned receive mailed surveys with either no compensation $5 check and call 3 weeks after mailing. Overall, 51.5% returned surveys. Comparison...
Prediction of protein subcellular location has currently become a hot topic because it been proven to be useful for understanding both the disease mechanisms and novel drug design. With rapid development automated microscopic imaging technology in recent years, classification methods bioimage-based have attracted considerable attention images can describe distribution intuitively detail. In current study, prediction method was proposed based on multi-view image features that are extracted...
Despite the current standard of care, breast cancer remains one leading causes mortality in women worldwide, thus emphasizing need for better predictive and therapeutic targets. ABI1 is associated with poor survival an aggressive phenotype, although its role tumorigenesis, metastasis, disease outcome to be elucidated. Here, we define ABI1-based seven-gene prognostic signature that predicts metastatic patients; essential component signature. Genetic disruption Abi1 primary tumors PyMT mice...
The article presents the temporal knowledge representation and its organization in a case-based reasoning system called MNAOMIA. general methodology is grounded on model of such that memory, learning are inseparable. This particular focus forces pertinent memory. main aspects dimension MNAOMIA detailed, as: language for cases, automatic trends from cases during process, memory generalization-based hierarchies under which indexed.