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Showing 20 of 299 academic articles

Causal analysis between altered levels of interleukins and obstructive sleep apnea

Minhan Yi, Minhan Yi, Minhan Yi, Wangcheng Zhao et al. • Frontiers in Immunology (2022)

BackgroundInflammation proteins including interleukins (ILs) have been reported to be related to obstructive sleep apnea (OSA). The aims of this study were to estimate the levels for several key interleukins in OSA and the causal effects be...

DOAJ Open Access (DOAJ) DOI: 10.3389/fimmu.2022.888644

Unlocking Clinical Data from Narrative Reports: A Study of Natural Language Processing

George M. Hripcsak, Carol Friedman, Philip O. Alderson, William DuMouchel et al. • Annals of Internal Medicine (1995)

OBJECTIVE: To evaluate the automated detection of clinical conditions described in narrative reports. DESIGN: Automated methods and human experts detected the presence or absence of six clinical conditions in 200 admission chest radiograph ...

OPENALEX DOI: https://doi.org/10.7326/0003-4819-122-9-199505010-00007

Menstrual Health Education Using a Specialized Large Language Model in India: Development and Evaluation Study of MenstLLaMA

Prottay Kumar Adhikary, Isha Motiyani, Gayatri Oke, Maithili Joshi et al. • Journal of Medical Internet Research (2025)

Abstract BackgroundThe quality and accessibility of menstrual health education (MHE) in low- and middle-income countries, including India, remain inadequate due to persistent challenges (eg, poverty, social stigma, and gender in...

DOAJ Open Access (DOAJ) DOI: 10.2196/71977

Revenue-sensitive evaluation of AI-assisted ICD-10-CM coding and human-AI collaboration under dual DRG payment systems

Ming-I. Chen, Ying-Lin Hsu, Yi-Hsin Chen • Scientific Reports (2026)

Abstract Automated ICD-10-CM coding is critical for hospital reimbursement under Diagnosis-Related Group (DRG) payment systems, yet standard metrics weight all errors equally. This study evaluated 11 models on MIMIC-IV under heterogeneous c...

DOAJ Open Access (DOAJ) DOI: 10.1038/s41598-026-57682-0

Thyroid Ultrasound Appropriateness Identification Through Natural Language Processing of Electronic Health Records

Cristian Soto Jacome, MD, Danny Segura Torres, MD, Jungwei W. Fan, PhD, Ricardo Loor-Torres, MD et al. • Mayo Clinic Proceedings: Digital Health (2024)

Objective: To address thyroid cancer overdiagnosis, we aim to develop a natural language processing (NLP) algorithm to determine the appropriateness of thyroid ultrasounds (TUS). Patients and Methods: Between 2017 and 2021, we identified 18...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.mcpdig.2024.01.001

Using 311 data to develop an algorithm to identify urban blight for public health improvement.

Jessica Athens, Setu Mehta, Sophie Wheelock, Nupur Chaudhury et al. • PLoS ONE (2020)

The growth of administrative data made available publicly, often in near-real time, offers new opportunities for monitoring conditions that impact community health. Urban blight-manifestations of adverse social processes in the urban enviro...

DOAJ Open Access (DOAJ) DOI: 10.1371/journal.pone.0235227

Natural Language Processing in Surgery

Joseph A. Mellia, Marten N. Basta, Yoshiko Toyoda, Sammy Othman et al. • Annals of Surgery (2020)

OBJECTIVE: The aim of this study was to systematically assess the application and potential benefits of natural language processing (NLP) in surgical outcomes research. SUMMARY BACKGROUND DATA: Widespread implementation of electronic health...

OPENALEX DOI: https://doi.org/10.1097/sla.0000000000004419

Integrating NLP to Enhance Algorithmic Identification of Metastatic and Castration‐Resistant Prostate Cancer in Large Claims‐Based Studies

Shannon R. Stock, Joshua A. Parrish, Michael T. Burns, Jessica L. Janes et al. • Cancer Medicine (2025)

ABSTRACT Purpose Accurate classification of prostate cancer (PC) disease states defined by the presence or absence of metastasis and castration resistance (CRPC) is critical but challenging in population‐based research. As chart review is n...

DOAJ Open Access (DOAJ) DOI: 10.1002/cam4.71406

Automated Burr Quality Classification in Drilling of AA6013 Aluminum Alloy Using YOLOv10n

Mikail Kırğıl, Suleyman Gokhan Taskin, Ali Ercetin • Applied Sciences (2026)

Burr formation during drilling of aluminum alloys can compromise hole quality and assembly accuracy, increasing the need for secondary deburring operations. The time-consuming and operator-dependent nature of manual visual inspection create...

DOAJ Open Access (DOAJ) DOI: 10.3390/app162010012

Reliable Parkinson’s Disease Detection by Analyzing Handwritten Drawings: Construction of an Unbiased Cascaded Learning System Based on Feature Selection and Adaptive Boosting Model

Liaqat Ali, Ce Zhu, Noorbakhsh Amiri Golilarz, Ashir Javeed et al. • IEEE Access (2019)

Parkinson's disease (PD) is the second most common neurodegenerative disease of central nervous system (CNS). Till now, there is no definitive clinical examination that can diagnose a PD patient. However, it has been reported that PD patien...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2019.2932037

TSER: A Two-Stage Character Segmentation Network With Two-Stream Attention and Edge Refinement

Jinyingming Zhang, Jin Liu, Xiongwei Xu, Peizhu Gong et al. • IEEE Access (2020)

Segmenting characters in an image is a classic yet challenging task in computer vision. Correctly determining boundaries of adhesive characters with various scales and shapes is essential for character segmentation, especially for separatin...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2020.3036545

Effectual pre-processing with quantization error elimination in pose detector with the aid of image-guided progressive graph convolution network (IGP-GCN) for multi-person pose estimation

Jhansi Rani Challapalli, Nagaraju Devarakonda • Machine Learning: Science and Technology (2023)

Multi-person pose estimation (MPE) remains a significant and intricate issue in computer vision. This is considered the human skeleton joint identification issue and resolved by the joint heat map regression network lately. Learning robust ...

DOAJ Open Access (DOAJ) DOI: 10.1088/2632-2153/acc9fc