AIMC Topic: Adult

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Common laboratory results-based artificial intelligence analysis achieves accurate classification of plasma cell dyscrasias.

PeerJ
BACKGROUND: Plasma cell dyscrasias encompass a diverse set of disorders, where early and precise diagnosis is essential for optimizing patient outcomes. Despite advancements, current diagnostic methodologies remain underutilized in applying artificia...

Using machine learning to classify temporomandibular disorders: a proof of concept.

Journal of applied oral science : revista FOB
BACKGROUND: the escalating influx of patients with temporomandibular disorders and the challenges associated with accurate diagnosis by non-specialized dental practitioners underscore the integration of artificial intelligence into the diagnostic pro...

Incorporating Generative AI to Promote Inquiry-Based Learning: Comparing Elicit AI Research Assistant to PubMed and CINAHL Complete.

Medical reference services quarterly
Generative artificial intelligence (GenAI) is transforming education, and faculty can either incorporate GenAI in intentional course design to promote inquiry-based learning (IBL) or resist its use. This study identified an effective strategy to inte...

Combination of Deep Learning Grad-CAM and Radiomics for Automatic Localization and Diagnosis of Architectural Distortion on DBT.

Academic radiology
RATIONALE AND OBJECTIVES: Detection and diagnosis of architectural distortion (AD) on digital breast tomosynthesis (DBT) is challenging. This study applied artificial intelligence (AI) using deep learning (DL) algorithms to detect AD, followed by rad...

A Stacked Multimodality Model Based on Functional MRI Features and Deep Learning Radiomics for Predicting the Early Response to Radiotherapy in Nasopharyngeal Carcinoma.

Academic radiology
BACKGROUND: This study aimed to construct and assess a comprehensive model that integrates MRI-derived deep learning radiomics, functional imaging (fMRI), and clinical indicators to predict early efficacy of radiotherapy in nasopharyngeal carcinoma (...

Identification of novel hypertension biomarkers using explainable AI and metabolomics.

Metabolomics : Official journal of the Metabolomic Society
BACKGROUND: The global incidence of hypertension, a condition of elevated blood pressure, is rising alarmingly. According to the World Health Organization's Qatar Hypertension Profile for 2023, around 33% of adults are affected by hypertension. This ...

Predicting the risk of pulmonary infection after kidney transplantation using machine learning methods: a retrospective cohort study.

International urology and nephrology
PURPOSE: Pulmonary infection is the most common and serious complication after kidney transplantation that affects the survival of the transplanted kidney and the quality of life of patients. This study aims to construct a machine learning model for ...

A protocol for trustworthy EEG decoding with neural networks.

Neural networks : the official journal of the International Neural Network Society
Deep learning solutions have rapidly emerged for EEG decoding, achieving state-of-the-art performance on a variety of decoding tasks. Despite their high performance, existing solutions do not fully address the challenge posed by the introduction of m...

Combination of plasma-based lipidomics and machine learning provides a useful diagnostic tool for ovarian cancer.

Journal of pharmaceutical and biomedical analysis
Ovarian cancer (OC), the second leading cause of death among gynecological cancers, is often diagnosed at an advanced stage due to its asymptomatic nature at early stages. This study aimed to explore the diagnostic potential of plasma-based lipidomic...

Exploring patient stratification in head and neck squamous cell carcinoma using machine learning techniques: Preliminary results.

Current problems in cancer
BACKGROUND: Head and Neck Squamous Cell Carcinoma (HNSCC) presents a significant challenge in oncology due to its inherent heterogeneity. Traditional staging systems, such as TNM (Tumor, Node, Metastasis), provide limited information regarding patien...