Skip Content
You are currently on the new version of our website. Access the old version .

BioMedInformatics, Volume 5, Issue 2

2025 June - 16 articles

Cover Story: Survival analysis is a statistical approach widely employed to model the time at which a clinical event starts on the basis of known clinical variables (covariates). Classical approaches such as Cox regression assume a linear relationship between a model’s covariates. Neural network models can overcome the intrinsic limitations of standard linear models. We implemented a deep Cox neural network (Cox-net) to predict the time at which a cardiac event occurs using patient data collected from the Myocardial Iron Overload in Thalassemia (MIOT) project. Cox-net achieved a concordance index (c-index) of 0.812 ± 0.036, outperforming classical Cox regression (0.790 ± 0.040), and also demonstrated resilience to varying levels of censored patients. A permutation feature importance analysis identified fibrosis and sex as the most significant predictors. View this paper
  • Issues are regarded as officially published after their release is announced to the table of contents alert mailing list .
  • You may sign up for email alerts to receive table of contents of newly released issues.
  • PDF is the official format for papers published in both, html and pdf forms. To view the papers in pdf format, click on the "PDF Full-text" link, and use the free Adobe Reader to open them.

Articles (16)

  • Article
  • Open Access
1,899 Views
12 Pages

Identification of a New Lung Cancer Biomarker Signature Using Data Mining and Preliminary In Vitro Validation

  • Ferid Ben Ali,
  • Denis Mustafov,
  • Maria Braoudaki,
  • Sola Adeleke and
  • Iosif Mporas

Background: Lung adenocarcinoma is one of the major subtype of non-Small Cell Lung Cancer and biomarkers are essential to be identified for early diagnosis. The study aims to find in silico and preliminary in vitro analysis of potential biomarkers fo...

  • Article
  • Open Access
1 Citations
3,349 Views
20 Pages

Voice as a Health Indicator: The Use of Sound Analysis and AI for Monitoring Respiratory Function

  • Nicki Lentz-Nielsen,
  • Lars Maaløe,
  • Pascal Madeleine and
  • Stig Nikolaj Blomberg

Background: Chronic obstructive pulmonary disease (COPD) is projected to be the third-leading cause of death by 2030. Traditional spirometry for the monitoring of the forced expiratory volume in one second (FEV1) can provoke discomfort and anxiety. T...

  • Article
  • Open Access
6 Citations
6,001 Views
33 Pages

Enhanced Brain Tumor Classification Using MobileNetV2: A Comprehensive Preprocessing and Fine-Tuning Approach

  • Md Atiqur Rahman,
  • Mohammad Badrul Alam Miah,
  • Md. Abir Hossain and
  • A. S. M. Sanwar Hosen

Background: Brain tumors are among the most difficult diseases to deal with in modern medicine due to the uncontrolled cell proliferation, which causes grave damage to the nervous system. Brain tumors can be broadly classified into two categories: pr...

  • Article
  • Open Access
2,473 Views
22 Pages

Anticancer Effects of Pleurotus salmoneostramineus Protein Hydrolysate on HepG2 Cells and In Silico Characterization of Structural Effects of Chromoprotein-Derived Peptides on the Mitochondrial Uncoupling Protein 2 (UCP2)

  • Erica K. Ventura-García,
  • Mónica A. Valdez-Solana,
  • Claudia Avitia-Domínguez,
  • Guadalupe García-Arenas,
  • Alfredo Téllez-Valencia,
  • Nagamani Balagurusamy and
  • Erick Sierra-Campos

Background: Pleurotus salmoneostramineus is acknowledged as a reliable source of high-quality protein, with its protein concentrates, hydrolysates, and peptides potentially offering health benefits to humans. However, studies validating the medi...

  • Article
  • Open Access
1,649 Views
22 Pages

Causal Discovery for Patient Classification Using Health-Related Quality of Life Questionnaires

  • Maria Ganopoulou,
  • Konstantinos Fokianos,
  • Christos Bakirtzis,
  • Lefteris Angelis and
  • Theodoros Moysiadis

Background: Health-related quality of life (HRQoL) questionnaires are essential for understanding the physical, psychological, lifestyle, and social factors that impact patients’ well-being. Causal discovery demonstrates significant potential in this...

  • Article
  • Open Access
3,115 Views
17 Pages

A Tutorial Toolbox to Simplify Bioinformatics and Biostatistics Analyses of Microbial Omics Data in an Island Context

  • Isaure Quétel,
  • Sourakhata Tirera,
  • Damien Cazenave,
  • Nina Allouch,
  • Chloé Baum,
  • Yann Reynaud,
  • Degrâce Batantou Mabandza,
  • Virginie Nerrière,
  • Serge Vedy and
  • David Couvin
  • + 5 authors

Background: Bioinformatics is increasingly used in various scientific works. Large amounts of heterogeneous data are being generated these days. It is difficult to interpret and analyze these data effectively. Several software tools have been develop...

  • Article
  • Open Access
1 Citations
2,108 Views
16 Pages

Decision Trees for the Analysis of Gene Expression Levels of COVID-19: An Association with Alzheimer’s Disease

  • Jesús Alberto Torres-Sosa,
  • Gonzalo Emiliano Aranda-Abreu,
  • Nicandro Cruz-Ramírez and
  • Sonia Lilia Mestizo-Gutiérrez

COVID-19 has caused millions of deaths around the world. The respiratory system is the main target of this disease, but it has also been reported to attack the central nervous system, creating a neuroinflammatory environment with the release of proin...

  • Article
  • Open Access
1 Citations
4,788 Views
23 Pages

Performance Comparison of Large Language Models for Efficient Literature Screening

  • Maria Teresa Colangelo,
  • Stefano Guizzardi,
  • Marco Meleti,
  • Elena Calciolari and
  • Carlo Galli

Background: Systematic reviewers face a growing body of biomedical literature, making early-stage article screening increasingly time-consuming. In this study, we assessed six large language models (LLMs)—OpenHermes, Flan T5, GPT-2, Claude 3 Ha...

  • Article
  • Open Access
1 Citations
3,381 Views
19 Pages

Subject-Independent Cuff-Less Blood Pressure Monitoring via Multivariate Analysis of Finger/Toe Photoplethysmography and Electrocardiogram Data

  • Seyedmohsen Dehghanojamahalleh,
  • Peshala Thibbotuwawa Gamage,
  • Mohammad Ahmed,
  • Cassondra Petersen,
  • Brianna Matthew,
  • Kesha Hyacinth,
  • Yasith Weerasinghe,
  • Ersoy Subasi,
  • Munevver Mine Subasi and
  • Mehmet Kaya

(1) Background: Blood pressure (BP) variability is an important risk factor for cardiovascular diseases. Still, existing BP monitoring methods often require periodic cuff-based measurements, raising concerns about their accuracy and convenience. This...

  • Article
  • Open Access
1 Citations
2,616 Views
20 Pages

Background: This work presents an artificial intelligence-based algorithm for detecting Parkinson’s disease (PD) from voice signals. The detection of PD at pre-symptomatic stages is imperative to slow disease progression. Speech signal processi...

  • Review
  • Open Access
1 Citations
7,248 Views
14 Pages

Artificial Intelligence as Assessment Tool in Occupational Therapy: A Scoping Review

  • Christos Kokkotis,
  • Ioannis Kansizoglou,
  • Theodoros Stampoulis,
  • Erasmia Giannakou,
  • Panagiotis Siaperas,
  • Stavros Kallidis,
  • Maria Koutra,
  • Christina Koutra,
  • Anastasia Beneka and
  • Evangelos Bebetsos

Occupational therapy (OT) is vital in improving functional outcomes and aiding recovery for individuals with long-term disabilities, particularly those resulting from neurological diseases. Traditional assessment methods often rely on clinical judgme...

  • Article
  • Open Access
1,605 Views
20 Pages

Background: Radiomic features have been extensively used with machine learning and other Artificial Intelligence methods in medical imaging problems. Coronavirus Disease 2019 (COVID-19), which has been spreading worldwide since 2020, has motivated sc...

  • Review
  • Open Access
16 Citations
8,727 Views
26 Pages

Artificial Intelligence (AI) and deep learning models have revolutionized diagnosis, prognostication, and treatment planning by extracting complex patterns from medical images, enabling more accurate, personalized, and timely clinical decisions. Desp...

  • Article
  • Open Access
2,466 Views
14 Pages

Scouting Biomarkers for Alzheimer’s Disease via Network Analysis of Exosome Proteomics Data

  • Alexis Sagonas,
  • Avgi E. Apostolakou,
  • Zoi I. Litou,
  • Marianna H. Antonelou and
  • Vassiliki A. Iconomidou

Background: Exosomes are a group of extracellular vesicles that are released by almost all mammalian cell types and engage in intracellular communication. Studies conducted in recent years have shown that exosomes are involved in a variety of disease...

  • Article
  • Open Access
8 Citations
4,683 Views
29 Pages

Kidney disease poses a significant global health challenge, affecting millions and straining healthcare systems due to limited nephrology resources. This paper examines the transformative potential of Generative AI (GenAI), Large Language Models (LLM...

  • Article
  • Open Access
3,245 Views
18 Pages

Explainable Survival Analysis of Censored Clinical Data Using a Neural Network Approach

  • Lisa Anita De Santi,
  • Francesca Orlandini,
  • Vincenzo Positano,
  • Laura Pistoia,
  • Francesco Sorrentino,
  • Giuseppe Messina,
  • Maria Grazia Roberti,
  • Massimiliano Missere,
  • Nicolò Schicchi and
  • Antonella Meloni
  • + 3 authors

Survival analysis is a statistical approach widely employed to model the time of an event, such as a patient’s death. Classical approaches include the Kaplan–Meier estimator and Cox proportional hazards regression, which assume a linear r...

Get Alerted

Add your email address to receive forthcoming issues of this journal.

XFacebookLinkedIn
BioMedInformatics - ISSN 2673-7426