Reset
Showing 20 of 1,299 academic articles

The Microbiome Composition of a Man's Penis Predicts Incident Bacterial Vaginosis in His Female Sex Partner With High Accuracy

Supriya D. Mehta, Dan Zhao, Stefan J. Green, Walter Agingu et al. • Frontiers in Cellular and Infection Microbiology (2020)

Background: We determined the predictive accuracy of penile bacteria for incident BV in female sex partners. In this prospective cohort, we enrolled Kenyan men aged 18–35 and their female sex partners aged 16 and older. We assessed BV at ba...

DOAJ Open Access (DOAJ) DOI: 10.3389/fcimb.2020.00433

Using Network-Based Machine Learning to Predict Transcription Factors Involved in Drought Resistance

Chirag Gupta, Venkategowda Ramegowda, Supratim Basu, Andy Pereira • Frontiers in Genetics (2021)

Gene regulatory networks underpin stress response pathways in plants. However, parsing these networks to prioritize key genes underlying a particular trait is challenging. Here, we have built the Gene Regulation and Association Network (GRA...

DOAJ Open Access (DOAJ) DOI: 10.3389/fgene.2021.652189

Machine Learning and Data Mining Methods in Diabetes Research

Ioannis Kavakiotis, O. Tsave, Athanasios Salifoglou, Nicos Maglaveras et al. • Computational and Structural Biotechnology Journal (2017)

The remarkable advances in biotechnology and health sciences have led to a significant production of data, such as high throughput genetic data and clinical information, generated from large Electronic Health Records (EHRs). To this end, ap...

OPENALEX cc-by DOI: https://doi.org/10.1016/j.csbj.2016.12.005 PMC: 5257026

Machine learning unifies the modeling of materials and molecules

Albert P. Bartók, Sandip De, Carl R. Poelking, Noam Bernstein et al. • Science Advances (2017)

Determining the stability of molecules and condensed phases is the cornerstone of atomistic modeling, underpinning our understanding of chemical and materials properties and transformations. We show that a machine-learning model, based on a...

OPENALEX cc-by-nc DOI: https://doi.org/10.1126/sciadv.1701816 PMC: 5729016

Machine Learning in Orthopedics: A Literature Review

Federico Cabitza, Angela Locoro, Giuseppe Banfi • Frontiers in Bioengineering and Biotechnology (2018)

In this paper we present the findings of a systematic literature review covering the articles published in the last two decades in which the authors described the application of a machine learning technique and method to an orthopedic probl...

OPENALEX cc-by DOI: https://doi.org/10.3389/fbioe.2018.00075 PMC: 6030383

A 9-mRNA signature measured from whole blood by a prototype PCR panel predicts 28-day mortality upon admission of critically ill COVID-19 patients

Claire Tardiveau, Claire Tardiveau, Guillaume Monneret, Guillaume Monneret et al. • Frontiers in Immunology (2022)

Immune responses affiliated with COVID-19 severity have been characterized and associated with deleterious outcomes. These approaches were mainly based on research tools not usable in routine clinical practice at the bedside. We observed th...

DOAJ Open Access (DOAJ) DOI: 10.3389/fimmu.2022.1022750

Decentralized Distributed Sequential Neural Networks Inference on Low-Power Microcontrollers in Wireless Sensor Networks: A Predictive Maintenance Case Study

Yernazar Bolat, Iain Murray, Yifei Ren, Nasim Ferdosian • Sensors (2025)

The growing adoption of IoT applications has led to increased use of low-power microcontroller units (MCUs) for energy-efficient, local data processing. However, deploying deep neural networks (DNNs) on these constrained devices is challeng...

DOAJ Open Access (DOAJ) DOI: 10.3390/s25154595

Gut Microbiota and Targeted Biomarkers Analysis in Patients With Cognitive Impairment

Shourong Lu, Ying Yang, Qiao Xu, Shuqiang Wang et al. • Frontiers in Neurology (2022)

Gut microbial alteration is closely associated with brain disorders including cognitive impairment (CI). Gut microbes have the potential to predicate the development of diseases. However, the gut microbial markers for CI remain to be elucid...

DOAJ Open Access (DOAJ) DOI: 10.3389/fneur.2022.834403

A Sensor-to-API Data Infrastructure for Building Digital Twins: Harmonizing Multi-Rate IoT Energy and Indoor Data Streams for Proactive Analytics

J. W. Njoroge, M. Koeva, M. Farnaghi, D. Petrova-Antonova et al. • ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences (2026)

Digital twins are increasingly used in smart buildings to monitor energy use. This requires reliable sensor data, geospatial information, and semantically rich 3D building geometry. However, building sensor data often has inconsistent sampl...

DOAJ Open Access (DOAJ) DOI: 10.5194/isprs-annals-XII-4-W1-2026-251-2026

Perceptual-Preference-Based Touring Routes in Xishu Gardens Using Panoramic Digital-Twin Modeling

Xueqian Gong, Zhanyuan Zhu, Li Guo, Yong Zhong et al. • Land (2025)

Xishu Gardens, an exemplary narrative of classical Chinese gardens, faces challenges in preserving its commemorative spatial structures while accommodating modern visitors’ needs. While trajectory analysis is critical, existing studies stru...

DOAJ Open Access (DOAJ) DOI: 10.3390/land14050932

Machine Learning Methods for Histopathological Image Analysis

Daisuke Komura, Shumpei Ishikawa • Computational and Structural Biotechnology Journal (2018)

Abundant accumulation of digital histopathological images has led to the increased demand for their analysis, such as computer-aided diagnosis using machine learning techniques. However, digital pathological images and related tasks have so...

OPENALEX cc-by DOI: https://doi.org/10.1016/j.csbj.2018.01.001 PMC: 6158771

Accelerated Prediction of Terahertz Performance Metrics in GaN IMPATT Sources via Artificial Neural Networks

Santu Mondal, Sneha Ray, Aritra Acharyya, Rudra Sankar Dhar et al. • IEEE Access (2025)

This work investigates the application of artificial neural network (ANN)-based regression models to predict the static and dynamic characteristics of GaN impact avalanche transit time (IMPATT) sources in the terahertz (THz) frequency regim...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2025.3567410

Machine Learning in Enzyme Engineering

Stanislav Mazurenko, Zbyněk Prokop, Jiřı́ Damborský • ACS Catalysis (2019)

Abstract Enzyme engineering plays a central role in developing efficient biocatalysts for biotechnology, biomedicine, and life sciences. Apart from classical rational design and directed evolution approaches, machine learning methods have b...

OPENALEX other-oa DOI: https://doi.org/10.1021/acscatal.9b04321

Automated shape-based clustering of 3D immunoglobulin protein structures in chronic lymphocytic leukemia

Eleftheria Polychronidou, Ilias Kalamaras, Andreas Agathangelidis, Lesley-Ann Sutton et al. • BMC Bioinformatics (2018)

Abstract Background Although the etiology of chronic lymphocytic leukemia (CLL), the most common type of adult leukemia, is still unclear, strong evidence implicates antigen involvement in disease ontogeny and evolution. Primary and 3D stru...

DOAJ Open Access (DOAJ) DOI: 10.1186/s12859-018-2381-1

Synergistic multi-altimeter for estimating water level in the coastal zone of Beibu Gulf using SEL, ALES + and BFAST algorithms

Jiaoling Qin, Jiaoling Qin, Sunzhe Li, Sunzhe Li et al. • Frontiers in Marine Science (2023)

Accurately monitoring and predicting the large-scale dynamic changes of water levels in coastal zones is essential for its protection, restoration and sustainable development. However, there has been a challenge for achieving this goal usin...

DOAJ Open Access (DOAJ) DOI: 10.3389/fmars.2022.1113387