AIMC Topic: Adult

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Development of a diagnostic support system for the fibrosis of nonalcoholic fatty liver disease using artificial intelligence and deep learning.

The Kaohsiung journal of medical sciences
Liver fibrosis is a pathological condition characterized by the abnormal proliferation of liver tissue, subsequently able to progress to cirrhosis or possibly hepatocellular carcinoma. The development of artificial intelligence and deep learning have...

The utility of artificial intelligence in identifying radiological evidence of lung cancer and pulmonary tuberculosis in a high-burden tuberculosis setting.

South African medical journal = Suid-Afrikaanse tydskrif vir geneeskunde
BACKGROUND: Artificial intelligence (AI), using deep learning (DL) systems, can be utilised to detect radiological changes of various pulmonary diseases. Settings with a high burden of tuberculosis (TB) and people living with HIV can potentially bene...

Deep learning-based automatic measurement system for patellar height: a multicenter retrospective study.

Journal of orthopaedic surgery and research
BACKGROUND: The patellar height index is important; however, the measurement procedures are time-consuming and prone to significant variability among and within observers. We developed a deep learning-based automatic measurement system for the patell...

Interpretable machine learning model for predicting acute kidney injury in critically ill patients.

BMC medical informatics and decision making
BACKGROUND: This study aimed to create a method for promptly predicting acute kidney injury (AKI) in intensive care patients by applying interpretable, explainable artificial intelligence techniques.

Prognostic subgroups of chronic pain patients using latent variable mixture modeling within a supervised machine learning framework.

Scientific reports
The present study combined a supervised machine learning framework with an unsupervised method, finite mixture modeling, to identify prognostically meaningful subgroups of diverse chronic pain patients undergoing interdisciplinary treatment. Question...

Establishment of a risk prediction model for olfactory disorders in patients with transnasal pituitary tumors by machine learning.

Scientific reports
To construct a prediction model of olfactory dysfunction after transnasal sellar pituitary tumor resection based on machine learning algorithms. A cross-sectional study was conducted. From January to December 2022, 158 patients underwent transnasal s...

Enhancing classification accuracy of HRF signals in fNIRS using semi-supervised learning and filtering.

Progress in brain research
This paper introduces a novel approach to enhance the classification accuracy of hemodynamic response function (HRF) signals acquired through functional near-infrared spectroscopy (fNIRS). Leveraging a semi-supervised learning (SSL) framework alongsi...

Using Google web search to analyze and evaluate the application of ChatGPT in femoroacetabular impingement syndrome.

Frontiers in public health
BACKGROUND: Chat Generative Pre-trained Transformer (ChatGPT) is a new machine learning tool that allows patients to access health information online, specifically compared to Google, the most commonly used search engine in the United States. Patient...

Application of a transparent artificial intelligence algorithm for US adults in the obese category of weight.

PloS one
OBJECTIVE AND AIMS: Identification of associations between the obese category of weight in the general US population will continue to advance our understanding of the condition and allow clinicians, providers, communities, families, and individuals m...