AIMC Topic: Chronic Disease

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Machine Learning Model Predicts Postoperative Outcomes in Chronic Rhinosinusitis With Nasal Polyps.

Clinical otolaryngology : official journal of ENT-UK ; official journal of Netherlands Society for Oto-Rhino-Laryngology & Cervico-Facial Surgery
OBJECTIVE: Evaluating the possibility of predicting chronic rhinosinusitis with nasal polyps (CRSwNP) disease course using Artificial Intelligence.

Integrating multi-task and cost-sensitive learning for predicting mortality risk of chronic diseases in the elderly using real-world data.

International journal of medical informatics
BACKGROUND AND OBJECTIVE: Real-world data encompass population diversity, enabling insights into chronic disease mortality risk among the elderly. Deep learning excels on large datasets, offering promise for real-world data. However, current models f...

A chatbot based question and answer system for the auxiliary diagnosis of chronic diseases based on large language model.

Scientific reports
In recent years, artificial intelligence has made remarkable strides, improving various aspects of our daily lives. One notable application is in intelligent chatbots that use deep learning models. These systems have shown tremendous promise in the m...

AI Hesitancy and Acceptability-Perceptions of AI Chatbots for Chronic Health Management and Long COVID Support: Survey Study.

JMIR human factors
BACKGROUND: Artificial intelligence (AI) chatbots have the potential to assist individuals with chronic health conditions by providing tailored information, monitoring symptoms, and offering mental health support. Despite their potential benefits, re...

Evaluation of transfer ensemble learning-based convolutional neural network models for the identification of chronic gingivitis from oral photographs.

BMC oral health
BACKGROUND: To evaluate the performances of several advanced deep convolutional neural network models (AlexNet, VGG, GoogLeNet, ResNet) based on ensemble learning for recognizing chronic gingivitis from screening oral images.

Artificial intelligence for automatic detection and segmentation of nasal polyposis: a pilot study.

European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery
PURPOSE: Accurate diagnosis and quantification of polyps and symptoms are pivotal for planning the therapeutic strategy of Chronic rhinosinusitis with nasal polyposis (CRSwNP). This pilot study aimed to develop an artificial intelligence (AI)-based i...

GaitNet+ARL: A Deep Learning Algorithm for Interpretable Gait Analysis of Chronic Ankle Instability.

IEEE journal of biomedical and health informatics
Chronic ankle instability (CAI) is a major public health concern and adversely affects people's mobility and quality of life. Traditional assessment methods are subjective and qualitative by means of clinician observation and patient self-reporting, ...

Identification of chronic non-atrophic gastritis and intestinal metaplasia stages in the Correa's cascade through machine learning analyses of SERS spectral signature of non-invasively-collected human gastric fluid samples.

Biosensors & bioelectronics
The progression of gastric cancer involves a complex multi-stage process, with gastroscopy and biopsy being the standard procedures for diagnosing gastric diseases. This study introduces an innovative non-invasive approach to differentiate gastric di...

Robot-aided assessment and associated brain lesions of impaired ankle proprioception in chronic stroke.

Journal of neuroengineering and rehabilitation
BACKGROUND: Impaired ankle proprioception strongly predicts balance dysfunction in chronic stroke. However, only sparse data on ankle position sense and no systematic data on ankle motion sense dysfunction in stroke are available. Moreover, the lesio...