The amount of knowledge generates within Health Informatics has grown to be quite immeasurable, and analysis of this Big Data grants potentially limitless possibilities for knowledge to be gained. In addition, this information can improve the standard of healthcare offered to patients. However, there are a variety of issues that arise when handling these vast quantities of knowledge, especially the way to analyze this data in a reliable manner. The basic goal of Health Informatics is to require in world medical data from all levels of human existence to assist advance our understanding of drugs and practice. This paper will present current research using Big Data tools and approaches for the analysis of Health Informatics data gathered at multiple levels, including the molecular, tissue, patient, and population levels. In addition to turn-out data at multiple levels, multiple levels of questions are addressed: human-scale biology, clinical-scale, and epidemic-scale. We will also analyze and examine possible future work for every one of those areas, also as how combining data from each level may provide the foremost promising approach to gain the most knowledge in Health Informatics.
Research Article: Journal of Health & Medical Informatics
Research Article: Journal of Health & Medical Informatics
Mini Review: Journal of Health & Medical Informatics
Mini Review: Journal of Health & Medical Informatics
Review Article: Journal of Health & Medical Informatics
Review Article: Journal of Health & Medical Informatics
Editorial: Journal of Health & Medical Informatics
Editorial: Journal of Health & Medical Informatics
Research Article: Journal of Health & Medical Informatics
Research Article: Journal of Health & Medical Informatics
Scientific Tracks Abstracts: Cancer Science & Therapy
Scientific Tracks Abstracts: Cancer Science & Therapy
Keynote: Alternative & Integrative Medicine
Keynote: Alternative & Integrative Medicine
Scientific Tracks Abstracts: Nuclear Medicine & Radiation Therapy
Scientific Tracks Abstracts: Nuclear Medicine & Radiation Therapy
Scientific Tracks Abstracts: Cancer Science & Therapy
Scientific Tracks Abstracts: Cancer Science & Therapy
Posters-Accepted Abstracts: Journal of Bioengineering & Biomedical Science
Posters-Accepted Abstracts: Journal of Bioengineering & Biomedical Science
Journal of Health & Medical Informatics received 2700 citations as per Google Scholar report