Machine learning in medical applications: A review of state-of-the-art methods

M Shehab, L Abualigah, Q Shambour… - Computers in Biology …, 2022 - Elsevier
Applications of machine learning (ML) methods have been used extensively to solve various
complex challenges in recent years in various application areas, such as medical, financial …

Development of machine learning model for diagnostic disease prediction based on laboratory tests

DJ Park, MW Park, H Lee, YJ Kim, Y Kim, YH Park - Scientific reports, 2021 - nature.com
The use of deep learning and machine learning (ML) in medical science is increasing,
particularly in the visual, audio, and language data fields. We aimed to build a new …

Pentagalloyl glucose and its functional role in vascular health: Biomechanics and drug-delivery characteristics

SS Patnaik, DT Simionescu, CJ Goergen… - Annals of biomedical …, 2019 - Springer
Pentagalloyl glucose (PGG) is an elastin-stabilizing polyphenolic compound that has
significant biomedical benefits, such as being a free radical sink, an anti-inflammatory agent …

Use of machine learning for prediction of patient risk of postoperative complications after liver, pancreatic, and colorectal surgery

K Merath, JM Hyer, R Mehta, A Farooq… - Journal of …, 2020 - Elsevier
Background Surgical resection is the only potentially curative treatment for patients with
colorectal, liver, and pancreatic cancers. Although these procedures are performed with low …

[HTML][HTML] Application and utility of boosting machine learning model based on laboratory test in the differential diagnosis of non-COVID-19 pneumonia and COVID-19

SM Baik, KS Hong, DJ Park - Clinical Biochemistry, 2023 - Elsevier
Abstract Background Non-Coronavirus disease 2019 (COVID-19) pneumonia and COVID-
19 have similar clinical features but last for different periods, and consequently, require …

Development of machine-learning model to predict COVID-19 mortality: application of ensemble model and regarding feature impacts

SM Baik, M Lee, KS Hong, DJ Park - Diagnostics, 2022 - mdpi.com
This study was designed to develop machine-learning models to predict COVID-19 mortality
and identify its key features based on clinical characteristics and laboratory tests. For this …

Predicting abdominal aortic aneurysm growth using patient-oriented growth models with two-step Bayesian inference

E Akkoyun, ST Kwon, AC Acar, W Lee… - Computers in biology and …, 2020 - Elsevier
Objective For small abdominal aortic aneurysms (AAAs), a regular follow-up examination is
recommended every 12 months for AAAs of 30–39 mm and every six months for AAAs of 40 …

Deep learning approach for early prediction of COVID-19 mortality using chest X-ray and electronic health records

SM Baik, KS Hong, DJ Park - BMC bioinformatics, 2023 - Springer
Background An artificial-intelligence (AI) model for predicting the prognosis or mortality of
coronavirus disease 2019 (COVID-19) patients will allow efficient allocation of limited …

Discovering panel of autoantibodies for early detection of lung cancer based on focused protein array

D Jiang, X Zhang, M Liu, Y Wang, T Wang… - Frontiers in …, 2021 - frontiersin.org
Substantial studies indicate that autoantibodies to tumor-associated antigens (TAAbs) arise
in early stage of lung cancer (LC). However, since single TAAbs as non-invasive biomarkers …

Muscle plays a more superior role than fat in bone homeostasis: A cross-sectional study of old Asian people

C Liu, PY Wong, X Tong, SKH Chow… - Frontiers in …, 2023 - frontiersin.org
Objectives The aim of this study was to discover the role of fat and muscle in bone structures,
as well as the relationship between obesity and sarcopenia on age-related osteoporosis …