AIMC Topic: Humans

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Machine learning methods in predicting the risk of malignant transformation of oral potentially malignant disorders: A systematic review.

International journal of medical informatics
BACKGROUND: Oral Potentially Malignant Disorders (OPMDs) refer to a heterogenous group of clinical presentations with heightened rate of malignant transformation. Identification of risk levels in OPMDs is crucial to determine the need for active inte...

Artificial intelligence to advance acute and intensive care medicine.

Current opinion in critical care
PURPOSE OF REVIEW: This review explores recent key advancements in artificial intelligence for acute and intensive care medicine. As artificial intelligence rapidly evolves, this review aims to elucidate its current applications, future possibilities...

Machine Learning Analysis Using RNA Sequencing to Distinguish Neuromyelitis Optica from Multiple Sclerosis and Identify Therapeutic Candidates.

The Journal of molecular diagnostics : JMD
This study aims to identify RNA biomarkers distinguishing neuromyelitis optica (NMO) from relapsing-remitting multiple sclerosis (RRMS) and explore potential therapeutic applications leveraging machine learning (ML). An ensemble approach was develope...

Letter to the Editor: It takes one to know one-Machine learning for identifying OBGYN abstracts written by ChatGPT.

International journal of gynaecology and obstetrics: the official organ of the International Federation of Gynaecology and Obstetrics

Improving cervical cancer classification in PAP smear images with enhanced segmentation and deep progressive learning-based techniques.

Diagnostic cytopathology
OBJECTIVE: Cervical cancer, a prevalent and deadly disease among women, comes second only to breast cancer, with over 700 daily deaths. The Pap smear test is a widely utilized screening method for detecting cervical cancer in its early stages. Howeve...

Determination of minimum inhibitory concentrations using machine-learning-assisted agar dilution.

Microbiology spectrum
UNLABELLED: Effective policy to address the global threat of antimicrobial resistance requires robust antimicrobial susceptibility data. Traditional methods for measuring minimum inhibitory concentration (MIC) are resource intensive, subject to human...

Building large-scale registries from unstructured clinical notes using a low-resource natural language processing pipeline.

Artificial intelligence in medicine
Building clinical registries is an important step in clinical research and improvement of patient care quality. Natural Language Processing (NLP) methods have shown promising results in extracting valuable information from unstructured clinical notes...

A causality-inspired generalized model for automated pancreatic cancer diagnosis.

Medical image analysis
Pancreatic cancer (PC) is a severely malignant cancer variant with high mortality. Since PC has no obvious symptoms, most PC patients are belatedly diagnosed at advanced disease stages. Recently, artificial intelligence (AI) approaches have demonstra...

Automatic multi-view pose estimation in focused cardiac ultrasound.

Medical image analysis
Focused cardiac ultrasound (FoCUS) is a valuable point-of-care method for evaluating cardiovascular structures and function, but its scope is limited by equipment and operator's experience, resulting in primarily qualitative 2D exams. This study pres...

Exploring the NRF2-TP53 Signaling Network Through Machine Learning and Pan-Cancer Analysis: Identifying Potential targets for Cancer Prognosis Related to Oxidative Stress.

Advanced biology
Oxidative stress (OXS) is closely related to tumor prognosis and immune response, while TP53 integrated with NRF2 is closely associated with the regulation of cancer-related OXS. Hence, constructing a TP53-NRF2 integrated OXS signature of pan-cancer ...