On the discovery of hospital admission patterns—a clarification

Abstract

ognjen.arandjelvoic@gmail.com.

Intuitive and interpretable visual communication of a complex statistical model of disease progression and risk

“…In the context of the present work, of main interest is the information collected each time a patient is diagnosed with an ailment. In particular, the diagnosis is recorded using a standardized coding schema such as that provided by the International Statistical Classification of Diseases and Related Health Problems (ICD-10) [20] or the related Australian Refined Diagnosis-Related Groups (ARDRGs), which have hierarchical structures [3].…”

Towards sophisticated learning from EHRs: Increasing prediction specificity and accuracy using clinically meaningful risk criteria

“…The contributions of the present work, the problems it addresses, and limitations of previous work that it overcomes are best understood in the context of a successful, recently described algorithm for longitudinal diagnosis pattern extraction from EHRs described by Arandjelović [5], [7] and subsequently further developed by Vasiljeva and Arandjelović [20]. Hence we summarize its main features; the reader is referred to the original publication for an indepth description of the algorithm.…”

Identification of promising research directions using machine learning aided medical literature analysis

“…Large amounts of highly heterogeneous data types are pervasive in medicine. Usually the concept of so-called "big data" in medicine is associated with the analysis of Electronic Health Records [14], [4], [7], [22], [23], large scale sociodemographic surveys of death causes [19], social media mining for health related data [12] etc. Much less discussed and yet arguably no less important realm where the amount of information presents a challenge to the medical field is the medical literature corpus itself.…”