AI Researcher|MLOps Specialist|PhD in AI emp. Applications

Semantic Grouping of Features for Predictive Modeling in Machine Learning

Background Semantic grouping of features refers to organizing related features into meaningful clusters based on their inherent relationships or domain-specific knowledge. In predictive modeling, this process is crucial for improving model interpretability, performance, and robustness. By clustering features that share a common context or meaning, we can reduce dimensionality, simplify feature engineering, and potentially enhance…

Personalization of treatment based on biomarkers

Definition Central to the personalized medicine approach is the utilization of biomarkers—measurable indicators of biological processes, pathogenic processes, or pharmacologic responses to a therapeutic intervention. Biomarkers enable clinicians to make informed decisions about diagnosis, prognosis, and therapy selection, enhancing treatment efficacy and patient outcomes. Pharmacodynamic Biomarkers Pharmacodynamic biomarkers are crucial for assessing a drug’s biological…

Generalizing Machine Learning Pipelines: From Data Balancing to Model Evaluation

Implementation A generalized python code to be used for classification tasks. Sklearn, tensorflow and keras are the main libraries used. For inference examples use the following github link Usage • Data Loading: You can load data from any SQLite database or CSV file by specifying the path and, if necessary, the SQL query. • Preprocessing…

Blood exam classification for predicting defining factors in metabolic syndrome diagnosis and other related conditions

Abstract In this paper, we reported on recent findings from our research on investigating the link between a person’s standard biochemistry profile (based on blood exams), body mass index (BMI), metabolism as health state and Systolic Blood Pressure (SBP). Our current findings expand upon our previous related research, which was based on the use of…

Cognitive Network Evaluation Toolkit for Medical Domains (COGNET-MD) COGNET-MD

Abstract Large Language Models (LLMs) constitute a breakthrough state-of-the-art Artificial Intelligence (AI) technology which is rapidly evolving and promises to aid in medical diagnosis either by assisting doctors or by simulating a doctor’s workflow in more advanced and complex implementations. In this technical paper, we outline Cognitive Network Evaluation Toolkit for Medical Domains (COGNET-MD), which…