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Full-Text Articles in Physical Sciences and Mathematics
Predicting Mental Health Crisis In Veterans: Early Warning Signs, Precursors And Protective Factors, Priyanka Annapureddy
Predicting Mental Health Crisis In Veterans: Early Warning Signs, Precursors And Protective Factors, Priyanka Annapureddy
Dissertations (1934 -)
Mental Health (MH) conditions have recently increased to a large extent due to socio-demographic changes. Posttraumatic Stress Disorder (PTSD) is one of the most common mental health disorders prevalent in US. PTSD is even more troubling at double the rate in combat veterans leaving their service compared to general population. Severity of PTSD is associated with risk taking behaviors such as substance abuse, non-suicidal self-injury, and sexual risk behaviors. Psychological disorders are often preceded by early warning signs and recognizing the early warning signs of PTSD will help in preventing the returning or worsening of PTSD symptoms. Ecological momentary assessment …
A Smartphone-Based Non-Invasive Measurement System For Blood Constituents From Photoplethysmography (Ppg) And Fingertip Videos Illuminated With The Near-Infrared Leds, Md Hasanul Aziz
Dissertations (1934 -)
At least two billion people are affected by hemoglobin (Hgb), diabetic-related, and other blood-related diseases. Regular clinical assessments of these problems are conducted by analyzing venipuncture-obtained blood samples in laboratories. A non-invasive, cheap, point-of-care, and accurate test is needed everywhere. We started with Hgb measurement, and after an extensive literature survey, we came up with a non-invasive solution with 10-second Smartphone videos of the index fingertips using custom hardware sets to illuminate the fingers. We tested four lighting conditions with wavelengths in the near-infrared spectrum suggested by the absorption properties of two primary components of blood- oxygenated Hgb and plasma. …
Causal Inference In Healthcare: Approaches To Causal Modeling And Reasoning Through Graphical Causal Models, Riddhiman Adib
Causal Inference In Healthcare: Approaches To Causal Modeling And Reasoning Through Graphical Causal Models, Riddhiman Adib
Dissertations (1934 -)
In the era of big data, researchers have access to large healthcare datasets collected over a long period. These datasets hold valuable information, frequently investigated using traditional Machine Learning algorithms or Neural Networks. These algorithms perform great in finding patterns out of datasets (as a predictive machine); however, the models lack extensive interpretability to be used in the healthcare sector (as an explainable machine). Without exploring underlying causal relationships, the algorithms fail to explain their reasoning. Causal Inference, a relatively newer branch of Artificial Intelligence, deals with interpretability and portrays causal relationships in data through graphical models. It explores the …