AIMC Topic: Humans

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Effects of data transformation and model selection on feature importance in microbiome classification data.

Microbiome
BACKGROUND: Accurate classification of host phenotypes from microbiome data is crucial for advancing microbiome-based therapies, with machine learning offering effective solutions. However, the complexity of the gut microbiome, data sparsity, composi...

Forecasting cardiovascular disease mortality using artificial neural networks in Sindh, Pakistan.

BMC public health
Cardiovascular disease (CVD) is a leading cause of death and disability worldwide, and its incidence and prevalence are increasing in many countries. Modeling of CVD plays a crucial role in understanding the trend of CVD death cases, evaluating the e...

Preoperative prediction of the selection of the NOTES approach for patients with symptomatic simple renal cysts via an interpretable machine learning model: a retrospective study of 264 patients.

Langenbeck's archives of surgery
BACKGROUND: There are multiple surgical approaches for treating symptomatic simple renal cysts (SSRCs). The natural orifice transluminal endoscopic surgery (NOTES) approach has gradually been applied as an emerging minimally invasive approach for the...

Assessing the feasibility and external validity of natural language processing-extracted data for advanced lung cancer patients.

Lung cancer (Amsterdam, Netherlands)
BACKGROUND: Manual extraction of real-world clinical data for research can be time-consuming and prone to error. We assessed the feasibility of using natural language processing (NLP), an AI technique, to automate data extraction for patients with ad...

Identification of optimal portal pressure decrease to control ascites while minimizing HE after TIPS: A multicenter study.

Hepatology (Baltimore, Md.)
BACKGROUND AND AIMS: Clinically significant portal hypertension in patients with liver cirrhosis can lead to refractory ascites. A TIPS treats clinically significant portal hypertension but may cause overt hepatic encephalopathy (oHE). Our aim was to...

The use of artificial intelligence in predicting maximal intercuspal position: A feasibility study.

Journal of prosthodontic research
PURPOSE: Artificial intelligence (AI) may be used to learn and predict the maxillomandibular relationship, particularly when the number of occluding teeth pairs is insufficient. This study aimed to investigate the feasibility of training a new two-st...

Exploring the potential of machine learning models to predict nasal measurements through facial landmarks.

The Journal of prosthetic dentistry
STATEMENT OF PROBLEM: Information on predicting the measurements of the nose from selected facial landmarks to assist in maxillofacial prosthodontics is lacking.

Predicting intermediate-risk prostate cancer using machine learning.

International urology and nephrology
PURPOSES: Intermediate-risk prostate cancer (IR PCa) is the most common risk group for localized prostate cancer. This study aimed to develop a machine learning (ML) model that utilizes biopsy predictors to estimate the probability of IR PCa and asse...

A discriminative multi-modal adaptation neural network model for video action recognition.

Neural networks : the official journal of the International Neural Network Society
Research on video-based understanding and learning has attracted widespread interest and has been adopted in various real applications, such as e-healthcare, action recognition, affective computing, to name a few. Amongst them, video-based action rec...