Artificial intelligence-assisted diagnostic cytology and genomic testing for hematologic disorders

L Gedefaw, CF Liu, RKL Ip, HF Tse, MHY Yeung… - Cells, 2023 - mdpi.com
Artificial intelligence (AI) is a rapidly evolving field of computer science that involves the
development of computational programs that can mimic human intelligence. In particular …

Machine learning and artificial intelligence in haematology

R Shouval, JA Fein, B Savani, M Mohty… - British journal of …, 2021 - Wiley Online Library
Digitalization of the medical record and integration of genomic methods into clinical practice
have resulted in an unprecedented wealth of data. Machine learning is a subdomain of …

Utilization of machine-learning models to accurately predict the risk for critical COVID-19

D Assaf, Y Gutman, Y Neuman, G Segal, S Amit… - Internal and emergency …, 2020 - Springer
Among patients with Coronavirus disease (COVID-19), the ability to identify patients at risk
for deterioration during their hospital stay is essential for effective patient allocation and …

Machine learning algorithms for predicting the recurrence of stage IV colorectal cancer after tumor resection

Y Xu, L Ju, J Tong, CM Zhou, JJ Yang - Scientific reports, 2020 - nature.com
The aim of this study is to explore the feasibility of using machine learning (ML) technology
to predict postoperative recurrence risk among stage IV colorectal cancer patients. Four …

[HTML][HTML] A review of artificial intelligence applications in hematology management: current practices and future prospects

Y El Alaoui, A Elomri, M Qaraqe… - Journal of Medical …, 2022 - jmir.org
Background Machine learning (ML) and deep learning (DL) methods have recently
garnered a great deal of attention in the field of cancer research by making a noticeable …

A comprehensive review of FET‐based pH sensors: materials, fabrication technologies, and modeling

S Sinha, T Pal - Electrochemical Science Advances, 2022 - Wiley Online Library
The demand for miniaturized point‐of‐care chemical/biochemical sensors has driven the
development of field‐effect transistors (FETs) based pH sensors over the last 50 years. This …

Physico-chemical and adsorption study of hydrothermally treated zeolite A and FAU-type zeolite X prepared from LD (Linz–Donawitz) slag of the steel industry

NS Samanta, PP Das, P Mondal, U Bora… - International Journal of …, 2024 - Taylor & Francis
Sodium-rich zeolite A and zeolite X (FAU-type) samples were synthesised from LD-slag via
fusion-assisted hydrothermal treatment. The physicochemical and thermal stability of the …

Identification of significant risks in pediatric acute lymphoblastic leukemia (ALL) through machine learning (ML) approach

N Mahmood, S Shahid, T Bakhshi, S Riaz… - Medical & Biological …, 2020 - Springer
Pediatric acute lymphoblastic leukemia (ALL) through machine learning (ML) technique was
analyzed to determine the significance of clinical and phenotypic variables as well as …

A machine learning approach to personalized dose adjustment of lamotrigine using noninvasive clinical parameters

X Zhu, W Huang, H Lu, Z Wang, X Ni, J Hu, S Deng… - Scientific Reports, 2021 - nature.com
The pharmacokinetic variability of lamotrigine (LTG) plays a significant role in its dosing
requirements. Our goal here was to use noninvasive clinical parameters to predict the dose …

Clinical data prediction model to identify patients with early-stage pancreatic cancer

Q Chen, DR Cherry, V Nalawade, EM Qiao… - JCO clinical cancer …, 2021 - ascopubs.org
PURPOSE Pancreatic cancer is an aggressive malignancy with patients often experiencing
nonspecific symptoms before diagnosis. This study evaluates a machine learning approach …