Reset
Showing 20 of 295 academic articles

Deep learning for computational chemistry

Garrett B. Goh, Nathan O. Hodas, Abhinav Vishnu • Journal of Computational Chemistry (2017)

The rise and fall of artificial neural networks is well documented in the scientific literature of both computer science and computational chemistry. Yet almost two decades later, we are now seeing a resurgence of interest in deep learning,...

OPENALEX Open Access DOI: https://doi.org/10.1002/jcc.24764

A Cardiovascular Disease Prediction Model Based on Routine Physical Examination Indicators Using Machine Learning Methods: A Cohort Study

Xin Qian, Yu Li, Xianghui Zhang, Heng Guo et al. • Frontiers in Cardiovascular Medicine (2022)

BackgroundCardiovascular diseases (CVD) are currently the leading cause of premature death worldwide. Model-based early detection of high-risk populations for CVD is the key to CVD prevention. Thus, this research aimed to use machine learni...

DOAJ Open Access (DOAJ) DOI: 10.3389/fcvm.2022.854287

Machine learning for advanced energy materials

Liu Yun, Oladapo Christopher Esan, Zhefei Pan, Liang An • Energy and AI (2021)

The screening of advanced materials coupled with the modeling of their quantitative structural-activity relationships has recently become one of the hot and trending topics in energy materials due to the diverse challenges, including low su...

OPENALEX cc-by-nc-nd DOI: https://doi.org/10.1016/j.egyai.2021.100049

A cascaded classification approach using transfer learning and feature engineering for improved breast cancer classification

Chokri Ferkous, Ouissal Fadel, Abderrahmane Kefali, Hayet-Farida Merouani • IJAIN (International Journal of Advances in Intelligent Informatics) (2026)

The primary objective of this study is to design a cascaded classification framework that integrates deep-learning representations with handcrafted and clinical features to enhance the reliability and accuracy of breast cancer detection in ...

DOAJ Open Access (DOAJ) DOI: 10.26555/ijain.v12i1.1670

High temperature Nb-Si alloys using data science: optimization of fracture toughness and high-temperature strength

Chao Xu, Dezhi Chen, Xiaofu Zhang, Qi Wang et al. • Nature Communications (2026)

Abstract High temperature Nb-Si based alloys face a critical challenge: achieving adequate room-temperature fracture toughness ( > 18 MPa·m1/2) for processing while maintaining high-temperature strength, properties that typically compete wi...

DOAJ Open Access (DOAJ) DOI: 10.1038/s41467-026-75353-6

Machine Learning in Virtual Screening

James L. Melville, Edmund K. Burke, Jonathan D. Hirst • Combinatorial Chemistry & High Throughput Screening (2009)

In this review, we highlight recent applications of machine learning to virtual screening, focusing on the use of supervised techniques to train statistical learning algorithms to prioritize databases of molecules as active against a partic...

OPENALEX DOI: https://doi.org/10.2174/138620709788167980

PosturAll: A Posture Assessment Software for Children

Ana Beatriz Neves, Rodrigo Martins, Nuno Matela, Tiago Atalaia • Bioengineering (2023)

From an early age, people are exposed to risk factors that can lead to musculoskeletal disorders like low back pain, neck pain and scoliosis. Medical screenings at an early age might minimize their incidence. The study intends to improve a ...

DOAJ Open Access (DOAJ) DOI: 10.3390/bioengineering10101171

Directed Evolution of Near-Infrared Serotonin Nanosensors with Machine Learning-Based Screening

Seonghyeon An, Yeongjoo Suh, Payam Kelich, Dakyeon Lee et al. • Nanomaterials (2024)

In this study, we employed a novel approach to improve the serotonin-responsive ssDNA-wrapped single-walled carbon nanotube (ssDNA-SWCNT) nanosensors, combining directed evolution and machine learning-based prediction. Our iterative optimiz...

DOAJ Open Access (DOAJ) DOI: 10.3390/nano14030247

Economic Evaluations of Artificial Intelligence Implementation in Diabetic Retinopathy Screening

Ahmad Ahmad, Neily Zakiyah, Auliya A. Suwantika • Pharmacology and Clinical Pharmacy Research (2025)

Diabetic retinopathy (DR) is a common complication of diabetes that damages retinal blood vessels and can lead to vision impairment. The application of Artificial Intelligence (AI) in DR screening offers a promising alternative to conventio...

DOAJ Open Access (DOAJ) DOI: 10.15416/pcpr.v9i3.60068

Artificial intelligence in pancreatic cancer

Bowen Huang, Haoran Huang, Shuting Zhang, Dingyue Zhang et al. • Theranostics (2022)

Pancreatic cancer is the deadliest disease, with a five-year overall survival rate of just 11%. The pancreatic cancer patients diagnosed with early screening have a median overall survival of nearly ten years, compared with 1.5 years for th...

OPENALEX cc-by DOI: https://doi.org/10.7150/thno.77949 PMC: 9576619

Spatio-temporal assessment of Toumeyella parvicornis spread in mediterranean coastal pine forests through sentinel-2 data

Giovanni D’Amico • European Journal of Remote Sensing (2026)

Mediterranean coastal pine forests offer vital ecological and cultural benefits but face threats from climate change, urbanization, and pests. Among invasive agents, Toumeyella parvicornis is a severe threat to Pinus pinea along Italy's coa...

DOAJ Open Access (DOAJ) DOI: 10.1080/22797254.2026.2709014

A machine learning approach predicts future risk to suicidal ideation from social media data

Arunima Roy, Katerina Nikolitch, Rachel McGinn, Safiya Jinah et al. • npj Digital Medicine (2020)

Abstract Machine learning analysis of social media data represents a promising way to capture longitudinal environmental influences contributing to individual risk for suicidal thoughts and behaviors. Our objective was to generate an algori...

DOAJ Open Access (DOAJ) DOI: 10.1038/s41746-020-0287-6

Women’s perceptions and attitudes towards the use of AI in mammography in Sweden: a qualitative interview study

Jennifer Viberg Johansson, Karin Dembrower, Fredrik Strand, Åsa Grauman • BMJ Open (2024)

Background Understanding women’s perspectives can help to create an effective and acceptable artificial intelligence (AI) implementation for triaging mammograms, ensuring a high proportion of screening-detected cancer. This study aimed to e...

DOAJ Open Access (DOAJ) DOI: 10.1136/bmjopen-2024-084014