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Showing 20 of 1,074 academic articles

Unsupervised machine learning identifies distinct ALS molecular subtypes in post-mortem motor cortex and blood expression data

Heather Marriott, Renata Kabiljo, Guy P Hunt, Ahmad Al Khleifat et al. • Acta Neuropathologica Communications (2023)

Abstract Amyotrophic lateral sclerosis (ALS) displays considerable clinical and genetic heterogeneity. Machine learning approaches have previously been utilised for patient stratification in ALS as they can disentangle complex disease lands...

DOAJ Open Access (DOAJ) DOI: 10.1186/s40478-023-01686-8

An automated deep learning framework for brain tumor classification using MRI imagery

Muhammad Aamir, Ziaur Rahman, Uzair Aslam Bhatti, Waheed Ahmed Abro et al. • Scientific Reports (2025)

Abstract The precise and timely diagnosis of brain tumors is essential for accelerating patient recovery and preserving lives. Brain tumors exhibit a variety of sizes, shapes, and visual characteristics, requiring individualized treatment s...

DOAJ Open Access (DOAJ) DOI: 10.1038/s41598-025-02209-2

Radiomics and radiogenomics: extracting more information from medical images for the diagnosis and prognostic prediction of ovarian cancer

Song Zeng, Xin-Lu Wang, Hua Yang • Military Medical Research (2024)

Abstract Ovarian cancer (OC) remains one of the most lethal gynecological malignancies globally. Despite the implementation of various medical imaging approaches for OC screening, achieving accurate differential diagnosis of ovarian tumors ...

DOAJ Open Access (DOAJ) DOI: 10.1186/s40779-024-00580-1

Artificial intelligence in glaucoma

Chengjie Zheng, Thomas V. Johnson, Aakriti Garg Shukla, Michael Vincent Boland • Current Opinion in Ophthalmology (2018)

PURPOSE OF REVIEW: The use of computers has become increasingly relevant to medical decision-making, and artificial intelligence methods have recently demonstrated significant advances in medicine. We therefore provide an overview of curren...

OPENALEX DOI: https://doi.org/10.1097/icu.0000000000000552

A review of optimization strategies for deep and machine learning in diabetic macular edema

A. M. Mutawa, Khalid Sabti, Bibin Shalini Sundaram Thankaleela, Seemant Raizada • Frontiers in Artificial Intelligence (2026)

Diabetic macular edema (DME) is a primary contributor to visual impairment in diabetic patients, necessitating precise and prompt analysis for optimal treatment. Recent breakthroughs in deep learning (DL) and machine learning (ML) have yiel...

DOAJ Open Access (DOAJ) DOI: 10.3389/frai.2026.1684752

Predictive digital twin for optimizing patient-specific radiotherapy regimens under uncertainty in high-grade gliomas

Anirban Chaudhuri, Graham Pash, David A. Hormuth, David A. Hormuth et al. • Frontiers in Artificial Intelligence (2023)

We develop a methodology to create data-driven predictive digital twins for optimal risk-aware clinical decision-making. We illustrate the methodology as an enabler for an anticipatory personalized treatment that accounts for uncertainties ...

DOAJ Open Access (DOAJ) DOI: 10.3389/frai.2023.1222612

Prediction of homologous recombination deficiency from routine histology with attention-based multiple instance learning in nine different tumor types

Chiara Maria Lavinia Loeffler, Omar S. M. El Nahhas, Hannah Sophie Muti, Zunamys I. Carrero et al. • BMC Biology (2024)

Abstract Background Homologous recombination deficiency (HRD) is recognized as a pan-cancer predictive biomarker that potentially indicates who could benefit from treatment with PARP inhibitors (PARPi). Despite its clinical significance, HR...

DOAJ Open Access (DOAJ) DOI: 10.1186/s12915-024-02022-9

Artificial Intelligence and Acute Stroke Imaging

J.E. Soun, D.S. Chow, M. Nagamine, R.S. Takhtawala et al. • American Journal of Neuroradiology (2020)

Artificial intelligence technology is a rapidly expanding field with many applications in acute stroke imaging, including ischemic and hemorrhage subtypes. Early identification of acute stroke is critical for initiating prompt intervention ...

OPENALEX cc-by DOI: https://doi.org/10.3174/ajnr.a6883 PMC: 7814792

The potential for artificial intelligence in healthcare

Thomas H. Davenport, Ravi Kalakota • Future Healthcare Journal (2019)

The complexity and rise of data in healthcare means that artificial intelligence (AI) will increasingly be applied within the field. Several types of AI are already being employed by payers and providers of care, and life sciences companies...

OPENALEX cc-by-nc-nd DOI: https://doi.org/10.7861/futurehosp.6-2-94 PMC: 6616181

Preoperative and Prognostic Prediction of Microvascular Invasion in Hepatocellular Carcinoma: A Review Based on Artificial Intelligence

Yu Jiang Master of Engineering, Kang Wang Master of Medicine, Yu-Ran Wang Master of Engineering, Yan-Jun Xiang Master of Medicine et al. • Technology in Cancer Research & Treatment (2023)

Microvascular invasion of hepatocellular carcinoma is an important factor affecting tumor recurrence after liver resection and liver transplantation. There are many ways to classify microvascular invasion, however, an international consensu...

DOAJ Open Access (DOAJ) DOI: 10.1177/15330338231212726

Impact of AI-quantified fluid dynamics on visual outcomes over 5 years in patients with treatment-naïve nAMD from the FRB! registry

Philipp Fuchs, Ursula Schmidt-Erfurth, Leonard M. Coulibaly, Hrvoje Bogunovic et al. • Scientific Reports (2025)

Abstract To investigate the impact of retinal fluid dynamics on visual outcomes in patients with treatment-naïve neovascular age-related macular degeneration (nAMD) treated in the real world over 5 years using approved AI-based fluid monito...

DOAJ Open Access (DOAJ) DOI: 10.1038/s41598-025-17417-z

Artificial intelligence revolutionizing anesthesia management: advances and prospects in intelligent anesthesia technology

Yannan Cao, Yixin Wang, Hang Liu, Lei Wu • Frontiers in Medicine (2025)

With the development of artificial intelligence (AI), AI-related technologies are being applied in many fields of medicine. Anesthesia is now widely used in surgery, emergency resuscitation, pain treatment and other fields. However, differe...

DOAJ Open Access (DOAJ) DOI: 10.3389/fmed.2025.1571725

Sex-based differences in characteristics, management, and outcomes in heart failure with reduced ejection fraction

Christian Basile, Stefan D. Anker, Gianluigi Savarese • Global Cardiology (2025)

Heart failure with reduced ejection fraction (HFrEF) exhibits significant sex-based differences in clinical presentation, management, and outcomes. This study aimed to evaluate these differences using data from the Swedish Heart Failure Reg...

DOAJ Open Access (DOAJ) DOI: 10.4081/cardio.2025.73

Effect of robot-assisted gait training combined with electroacupuncture on lower limb motor function and brain network characteristics in stroke: an EEG study

Haiping Huang, Xinyi Su, Yuqian Zhang, Zhixi Liu et al. • Journal of NeuroEngineering and Rehabilitation (2025)

Abstract Background Stroke survivors often experience residual motor dysfunction in their limbs. Additional physical rehabilitation therapies may further improve patients’ functional outcomes. By combining direct interventions targeting the...

DOAJ Open Access (DOAJ) DOI: 10.1186/s12984-025-01827-1

An Ensemble Machine Learning Model for Early Prediction of Vancomycin-Induced Acute Kidney Injury in ICU Patients

Faezeh Aghamirzaei, Ahmad Ali Abin, Farzaneh Futuhi • Archives of Academic Emergency Medicine (2025)

Introduction: Acute Kidney Injury (AKI) is a severe complication of vancomycin treatment due to its nephrotoxic effects. However, research on predicting AKI in this high-risk group remains limited. This study presents a stacking ensemble ma...

DOAJ Open Access (DOAJ) DOI: 10.22037/aaemj.v13i1.2560

Artificial intelligence assisted 3D in the robotic urooncology? A systematic review and narrative synthesis of current applications, challenges and future directions

Bara Barakat, Bilal Al-Absi, Boris Hadaschik, Christian Rehme et al. • The Canadian Journal of Urology (2026)

Background: Artificial intelligence (AI)-assisted three-dimensional (3D) surgical platforms, integrated with augmented reality, have the potential to improve intraoperative anatomical recognition and provide surgeons with an immersive, dyna...

DOAJ Open Access (DOAJ) DOI: 10.32604/cju.2026.071284