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G-Aligner: a graph-based feature alignment method for untargeted LC–MS-based metabolomics

Ruimin Wang, Miaoshan Lu, Shaowei An, Jinyin Wang et al. • BMC Bioinformatics (2023)

Abstract Background Liquid chromatography–mass spectrometry is widely used in untargeted metabolomics for composition profiling. In multi-run analysis scenarios, features of each run are aligned into consensus features by feature alignment ...

DOAJ Open Access (DOAJ) DOI: 10.1186/s12859-023-05525-4

Performance of computational algorithms to deconvolve heterogeneous bulk ovarian tumor tissue depends on experimental factors

Ariel A. Hippen, Dalia K. Omran, Lukas M. Weber, Euihye Jung et al. • Genome Biology (2023)

Abstract Background Single-cell gene expression profiling provides unique opportunities to understand tumor heterogeneity and the tumor microenvironment. Because of cost and feasibility, profiling bulk tumors remains the primary population-...

DOAJ Open Access (DOAJ) DOI: 10.1186/s13059-023-03077-7

Behavioral dataset for Long-Evans and its schizophrenia-like substrain through several generations

Gábor Kőrösi, Oliver Czimbalmos, Gabriella Kekesi, Gyongyi Horvath • Scientific Data (2026)

Abstract We present a high-throughput behavioral dataset acquired with Ambitus, an automated reward-based corridor system that records locomotor and exploratory activities and cognitive functions after minimal handling. The collection conta...

DOAJ Open Access (DOAJ) DOI: 10.1038/s41597-026-06735-0

Artificial intelligence–aided diagnosis model for acute respiratory distress syndrome combining clinical data and chest radiographs

Kai-Chih Pai, Wen-Cheng Chao, Yu-Len Huang, Ruey-Kai Sheu et al. • Digital Health (2022)

Objective The aim of this study was to develop an artificial intelligence–based model to detect the presence of acute respiratory distress syndrome (ARDS) using clinical data and chest X-ray (CXR) data. Method The transfer learning method w...

DOAJ Open Access (DOAJ) DOI: 10.1177/20552076221120317

Development and validation of an interpretable machine learning model for predicting the risk of coronary heart disease risk in diabetes mellitus patients: a dual-center retrospective study

Ye Kuang, Yan Yu, Jing Li, Chuanmei Peng et al. • BMC Medical Informatics and Decision Making (2026)

Abstract Background Diabetes mellitus (DM) combined with coronary heart disease (CHD) significantly increases the risk of cardiovascular events with a greater mortality rate. Therefore, establishing a predictive model can help DM patients r...

DOAJ Open Access (DOAJ) DOI: 10.1186/s12911-026-03461-w

Exploring feature selection and classification methods for predicting heart disease

Robinson Spencer, Fadi Thabtah, Neda Abdelhamid, Michael Thompson • Digital Health (2020)

Machine learning has been used successfully to improve the accuracy of computer-aided diagnosis systems. This paper experimentally assesses the performance of models derived by machine learning techniques by using relevant features chosen b...

DOAJ Open Access (DOAJ) DOI: 10.1177/2055207620914777

Integrating machine learning algorithms and explainable artificial intelligence approach for predicting patient unpunctuality in psychiatric clinics

Alireza Kasaie, Suchithra Rajendran • Healthcare Analytics (2023)

This study addresses patient unpunctuality, a major concern affecting patient waiting time, resource utilization, and quality of care. We develop and compare four machine learning models, including multinomial logistic regression, decision ...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.health.2023.100242

Central vein sign: A diagnostic biomarker in multiple sclerosis (CAVS-MS) study protocol for a prospective multicenter trial

D. Ontaneda, P. Sati, P. Raza, M. Kilbane et al. • NeuroImage: Clinical (2021)

The specificity and implementation of current MRI-based diagnostic criteria for multiple sclerosis (MS) are imperfect. Approximately 1 in 5 of individuals diagnosed with MS are eventually determined not to have the disease, with overrelianc...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.nicl.2021.102834

Argumentation approaches for explanaible AI in medical informatics

Luciano Caroprese, Eugenio Vocaturo, Ester Zumpano • Intelligent Systems with Applications (2022)

Artificial Intelligence algorithms are powerful in performing accurate predictions, but they are often considered black boxes as they do not provide any explanation about how outputs are derived from inputs or why a decision is taken. There...

OPENALEX cc-by-nc-nd DOI: https://doi.org/10.1016/j.iswa.2022.200109

Introduction to Medical Informatics

Joseph D. Bronzino, Donald R. Peterson • CRC Press eBooks (2014)

What is medical informatics? In the summer of 2004 I was invited to lecture at Dartmouth. Dr. Rosen, my host, asked me if I could address my interpretation of medical informatics during my lecture. This presentation made me review and refle...

OPENALEX DOI: https://doi.org/10.1201/b15468-65

Development and production of an oligonucleotide MuscleChip: use for validation of ambiguous ESTs

Lanfranchi Gerolamo, Teslovich Tanya M, Chen Yi-Wen, Toppo Stefano et al. • BMC Bioinformatics (2002)

Abstract Background We describe the development, validation, and use of a highly redundant 120,000 oligonucleotide microarray (MuscleChip) containing 4,601 probe sets representing 1,150 known genes expressed in muscle and 2,075 EST clusters...

DOAJ Open Access (DOAJ) DOI: 10.1186/1471-2105-3-33

Growing functional modules from a seed protein via integration of protein interaction and gene expression data

Dimitrakopoulou Konstantina, Maraziotis Ioannis A, Bezerianos Anastasios • BMC Bioinformatics (2007)

Abstract Background Nowadays modern biology aims at unravelling the strands of complex biological structures such as the protein-protein interaction (PPI) networks. A key concept in the organization of PPI networks is the existence of dense...

DOAJ Open Access (DOAJ) DOI: 10.1186/1471-2105-8-408

ANAT 2.0: reconstructing functional protein subnetworks

Yomtov Almozlino, Nir Atias, Dana Silverbush, Roded Sharan • BMC Bioinformatics (2017)

Abstract Background ANAT is a graphical, Cytoscape-based tool for the inference of protein networks that underlie a process of interest. The ANAT tool allows the user to perform network reconstruction under several scenarios in a number of ...

DOAJ Open Access (DOAJ) DOI: 10.1186/s12859-017-1932-1

Methods in Medical Informatics

Jules J. Berman • Chapman & Hall/CRC eBooks (2010)

Too often, healthcare workers are led to believe that medical informatics is a complex field that can only be mastered by teams of professional programmers. This is simply not the case. With just a few dozen simple algorithms, easily implem...

OPENALEX DOI: https://doi.org/10.1201/ebk1439841822

The Neuroscience of Language

Friedemann Pulvermüller A • Cambridge University Press eBooks (2003)

How is language organized in the human brain? The Neuroscience of Language, published in 2003, puts forth a systematic model of language to bridge the gap between linguistics and neuroscience. Neuronal models of word and serial order proces...

OPENALEX DOI: https://doi.org/10.1017/cbo9780511615528

Computational Tools; Indispensable Armamentarium of Medical Biotechnology

Nutan, Swapnil Jain, K Shilpa, Akanksha Tomar et al. • Indian Journal of Science and Technology (2016)

Objective: Computational infrastructure of medical biotechnology provides insight into elements of genomics, proteomics for understanding diseases and biological systems in a more comprehensive and systematic way. The present study exclusiv...

OPENALEX cc-by DOI: https://doi.org/10.17485/ijst/2016/v9i32/100745

O PROBLEMATIZARE A BUNEI GUVERNĂRI DIGITALE

Șerban. Henrieta • Revista de Știinţe Politice şi Relaţii Internaţionale (2025)

In political science today, the notions of “governance“ and “good governance“ compete as synonyms. The negative connotations of the first term (from the sphere of significance of the idea of leadership, or also care for one or more minors o...

DOAJ Open Access (DOAJ)

An integrated vehicle routing model to optimize agricultural products distribution in retail chains

W. Madushan Fernando, Amila Thibbotuwawa, H. Niles Perera, Peter Nielsen et al. • Cleaner Logistics and Supply Chain (2024)

The Vehicle Routing Problem (VRP) represents a thoroughly investigated domain within operations research, yielding substantial cost savings in global transportation. The fundamental objective of the VRP is to determine the optimal route pla...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.clscn.2023.100137

A novel chaotic flower pollination algorithm for function optimization and constrained optimal power flow considering renewable energy sources

Fatima Daqaq, Fatima Daqaq, Mohammed Ouassaid, Salah Kamel et al. • Frontiers in Energy Research (2022)

This study presents an improved chaotic flower pollination algorithm (CFPA) with a view to handle the optimal power flow (OPF) problem integrating a hybrid wind and solar power and generate the optimal settings of generator power, bus volta...

DOAJ Open Access (DOAJ) DOI: 10.3389/fenrg.2022.941705

Exact and Evolutionary Algorithms for Synchronization of Public Transportation Timetables Considering Extended Transfer Zones

Sergio Nesmachnow, Claudio Risso • Applied Sciences (2021)

This article addresses timetable synchronization in public transportation, an important problem in modern smart cities, in order to guarantee a proper quality of service to citizens. Two variants of the bus timetabling synchronization probl...

DOAJ Open Access (DOAJ) DOI: 10.3390/app11157138