Learn how using historical data, instead of standard deviation, offers a more accurate assessment of stock volatility and risk management strategies.

Data Normalization vs. Standardization is one of the most foundational yet often misunderstood topics in machine learning and ...

Introduction Dyspnoea is an existentially burdensome symptom in patients with advanced and progressive diseases such as cancer, chronic obstructive pulmonary disease (COPD) and advanced heart failure.

Optokinetic Nystagmus (OKN) is a natural reflexive eye movement in oculomotor studies, reflecting the health status of the visual system. Through accurate eye center annotation, physicians can observe ...

Guggenheim Securities Emerging Outlook: Biotech Summit 2026 February 12, 2026 12:30 PM ESTCompany ParticipantsR.

Diop, T., Samb, C.O., Diop, A.B., Fall, L., Cisse, O., Diouf, C. and Scholte, P. (2026) Resource-Use Conflicts in the Bamboung Marine Protected Area (Fatick, Senegal). Open Journal of Ecology, 16, ...

Risk prediction has been used in the primary prevention of cardiovascular disease for >3 decades. Contemporary cardiovascular risk assessment relies on multivariable models, which integrate ...

Public health recommendations suggest individuals can resume normal activities 5 days after symptom cessation. However, our study finds that full recovery can take longer, indicating that delayed ...

Abstract: Side-channel techniques, such as Distance-of-Means and Kolmogorov-Smirnov analysis, provide valuable insights about leakages from the indirect perspectives of statistical moment and ...

Statistical mechanics constitutes one of the pillars of contemporary physics. Recognized as such - together with mechanics (classical, quantum, relativistic), electromagnetism and thermodynamics -, it ...

Background/objectives: The existing literature on normative data for accommodative facility (AF) in African populations is limited to high school students. There is no normative data for vergence ...

Abstract: One of the essential steps in machine learning is data cleaning during the preprocessing phase. In this step, it is necessary to remove incorrect, damaged, or clearly skewed data, often ...