Related papers: Analyses and Concerns in Precision Medicine: A Sta…
Machine learning methods in healthcare have traditionally focused on using data from a single modality, limiting their ability to effectively replicate the clinical practice of integrating multiple sources of information for improved…
Research is a tertiary priority in the EHR, where the priorities are patient care and billing. Because of this, the data is not standardized or formatted in a manner easily adapted to machine learning approaches. Data may be missing for a…
The essence of precision oncology lies in its commitment to tailor targeted treatments and care measures to each patient based on the individual characteristics of the tumor. The inherent heterogeneity of tumors necessitates gathering…
Over the past two decades, the field of high-dimensional statistics has experienced substantial progress, driven largely by technological advances that have dramatically reduced the cost and effort for data collection and storage across a…
Industrial Revolution 4.0 transforms healthcare systems. The first three technological revolutions changed the relationship between human and machine interaction due to the exponential growth of machine numbers. The fourth revolution put…
The field of Clinical-Computational Nuclear Medicine is rapidly advancing, fueled by AI, tracer kinetic modeling, radiomics, and integrated informatics. These technologies improve imaging quality, automate lesion detection, and enable…
Artificial intelligence has provided us with an exploration of a whole new research era. As more data and better computational power become available, the approach is being implemented in various fields. The demand for it in health…
This paper explores the advancements and applications of language models in healthcare, focusing on their clinical use cases. It examines the evolution from early encoder-based systems requiring extensive fine-tuning to state-of-the-art…
Heart Disease has become one of the most serious diseases that has a significant impact on human life. It has emerged as one of the leading causes of mortality among the people across the globe during the last decade. In order to prevent…
Data scientists and statisticians are often at odds when determining the best approach, machine learning or statistical modeling, to solve an analytics challenge. However, machine learning and statistical modeling are more cousins than…
Machine learning can be used to make sense of healthcare data. Probabilistic machine learning models help provide a complete picture of observed data in healthcare. In this review, we examine how probabilistic machine learning can advance…
Precision medicine incorporates patient-level covariates to tailor treatment decisions, seeking to improve outcomes. In longitudinal studies with time-varying covariates and sequential treatment decisions, precision medicine can be…
Personalized medicine has become an important part of medicine, for instance predicting individual drug responses based on genomic information. However, many current statistical methods are not tailored to this task, because they overlook…
The emerging era of personalized medicine relies on medical decisions, practices, and products being tailored to the individual patient. Point-of-care systems, at the heart of this model, play two important roles. First, they are required…
Big medical data poses great challenges to life scientists, clinicians, computer scientists, and engineers. In this paper, a group of life scientists, clinicians, computer scientists and engineers sit together to discuss several fundamental…
Medical images constitute a source of information essential for disease diagnosis, treatment and follow-up. In addition, due to its patient-specific nature, imaging information represents a critical component required for advancing…
The paper describes how the new technologies and data they generate are transforming medicine. It stresses the uniqueness of heterogeneous medical data and the ways of dealing with them. It lists different sources that generate big medical…
Research is ongoing all over the world for identifying the barriers and finding effective solutions to accelerate the projection of Precision Medicine (PM) in the healthcare industry. Yet there has not been a valid and practical model to…
Electronic health records are an increasingly important resource for understanding the interactions between patient health, environment, and clinical decisions. In this paper we report an empirical study of predictive modeling of several…
The development of high-throughput sequencing and targeted therapies has led to the emergence of personalized medicine: a patient's molecular profile or the presence of a specific biomarker of drug response will correspond to a treatment…