What are Microservices Microservices – also known as the microservice architecture – is a software development paradigm, where an application is structured as a collection of services that are easier to maintain and test, loosely coupled and independently deployable. The microservice architecture enables a fast and reliable delivery of large and highly complex applications with…
In brief Explainable artificial intelligence (XAI) is the process of making the outcome of non-linearly programmed systems more transparent, in an effort to avoid “black-box” processes. XAI in Computer Science is defined by tools and frameworks to help in understanding and interpret predictions made by the various machine learning models. Libraries The most commonly used…
The background According to the Technology Acceptance Model (TAM), the acceptance of new technological systems depends on two external factors which are considered as measurements of intention to use and likelihood of adoption. The users’ perception of value extraction from that technology is defined as perceived usefulness. The level of effort as a usability parameter…
Abstract The developed approach in this research, centers around personalisation derived from targeted clustering techniques based on the principles of the Technology Acceptance Model – TAM. By employing targeted clustering, we create tailored explanations for users based on their unique characteristics and requirements. To validate the effectiveness of our methodology, we conducted a case study…
The Transformer model has been very influential in the field of NLP and constitutes the engine of the state-of-the-art LLMs, still powering the ChatGPT engines as of the time of the writing. In the following the architecture of a Transformer is presented, along with a description of each step and a brief explanation of the related…
The approach The diagnostic procedure in medicine often combines different approaches, which are influenced by the context, patient symptoms, clinician expertise, and available diagnostic tools [1]. As illustrated and summarized in the following figure, the diagnostic process begins with gathering patient data, including a medical history and possibly a physical examination. This information is then…
Parameters main(q, d, m): The primary function that takes in the Question (q), Domain (d), and Medical (m) parameters and returns the Answer (a) and Grade (grade). • Decision Logic: Implements the conditional logic as per the pseudocode to determine the appropriate answer a. • answer_content(): A placeholder function to generate the answer content c.…
Abstract In this paper, we present a novel Artificial Intelligence (AI) -empowered system that enhances large language models and other machine learning tools with rules to provide primary care diagnostic advice to patients. Specifically, we introduce a novel methodology, represented through a process diagram, which allows the definition of generative AI processes and functions with…
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…
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…