[HTML][HTML] Interpretable and explainable predictive machine learning models for data-driven protein engineering

D Medina-Ortiz, A Khalifeh, H Anvari-Kazemabad… - Biotechnology …, 2024 - Elsevier
Protein engineering through directed evolution and (semi) rational design has become a
powerful approach for optimizing and enhancing proteins with desired properties. The …

Application of Artificial Intelligence for Classification, Segmentation, Early Detection, Early Diagnosis, and Grading of Diabetic Retinopathy From Fundus Retinal …

G Rajarajeshwari, GC Selvi - IEEE Access, 2024 - ieeexplore.ieee.org
Diabetic Retinopathy (DR) remains a major factor contributing to vision loss worldwide,
particularly among individuals with diabetes. Timely and accurate diagnosis of DR is …

HOTGpred: Enhancing human O-linked threonine glycosylation prediction using integrated pretrained protein language model-based features and multi-stage feature …

NT Pham, Y Zhang, R Rakkiyappan… - Computers in Biology and …, 2024 - Elsevier
O-linked glycosylation is a complex post-translational modification (PTM) in human proteins
that plays a critical role in regulating various cellular metabolic and signaling pathways. In …

Artificial Intelligence in Point-of-Care Biosensing: Challenges and Opportunities

CD Flynn, D Chang - Diagnostics, 2024 - mdpi.com
The integration of artificial intelligence (AI) into point-of-care (POC) biosensing has the
potential to revolutionize diagnostic methodologies by offering rapid, accurate, and …

Interpretable (not just posthoc-explainable) medical claims modeling for discharge placement to reduce preventable all-cause readmissions or death

TL Chang, H Xia, S Mahajan, R Mahajan, J Maisog… - Plos one, 2024 - journals.plos.org
We developed an inherently interpretable multilevel Bayesian framework for representing
variation in regression coefficients that mimics the piecewise linearity of ReLU-activated …

Stacking with Recursive Feature Elimination-Isolation Forest for classification of diabetes mellitus

NF Idris, MA Ismail, MIM Jaya, AO Ibrahim… - Plos one, 2024 - journals.plos.org
Diabetes Mellitus is one of the oldest diseases known to humankind, dating back to ancient
Egypt. The disease is a chronic metabolic disorder that heavily burdens healthcare …

Pilot-Study to Explore Metabolic Signature of Type 2 Diabetes: A Pipeline of Tree-Based Machine Learning and Bioinformatics Techniques for Biomarkers Discovery

FH Yagin, F Al-Hashem, I Ahmad, F Ahmad… - Nutrients, 2024 - mdpi.com
Background: This study aims to identify unique metabolomics biomarkers associated with
Type 2 Diabetes (T2D) and develop an accurate diagnostics model using tree-based …

[HTML][HTML] Clinical applications of artificial intelligence in diabetes management: A bibliometric analysis and comprehensive review

A Daza, AJ Olivos-López, MC Pizarro… - Informatics in Medicine …, 2024 - Elsevier
Background Diabetes is one of the most common pathologies today and has become a
constant problem in public health worldwide. Objective The purpose of this study is to …

Machine learning-based identification and validation of immune-related biomarkers for early diagnosis and targeted therapy in diabetic retinopathy

Y Tao, M Xiong, Y Peng, L Yao, H Zhu, Q Zhou… - Gene, 2025 - Elsevier
The early diagnosis of diabetic retinopathy (DR) is challenging, highlighting the urgent need
to identify new biomarkers. Immune responses play a crucial role in DR, yet there are …

Novel approach exploring the correlation between presepsin and routine laboratory parameters using explainable artificial intelligence

JS Jeong, T Kang, H Ju, CH Cho - Heliyon, 2024 - cell.com
Although presepsin, a crucial biomarker for the diagnosis and management of sepsis, has
gained prominence in contemporary medical research, its relationship with routine …