AIMC Topic: Machine Learning

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Rapid and accurate multi-phenotype imputation for millions of individuals.

Nature communications
Deep phenotyping can enhance the power of genetic analysis, including genome-wide association studies (GWAS), but the occurrence of missing phenotypes compromises the potential of such resources. Although many phenotypic imputation methods have been ...

Machine learning models predicting risk of revision or secondary knee injury after anterior cruciate ligament reconstruction demonstrate variable discriminatory and accuracy performance: a systematic review.

BMC musculoskeletal disorders
BACKGROUND: To summarize the statistical performance of machine learning in predicting revision, secondary knee injury, or reoperations following anterior cruciate ligament reconstruction (ACLR), and to provide a general overview of the statistical p...

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...

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...

Exploring spatio-temporal heterogeneity of rural settlement patterns on carbon emission across more than 2800 Chinese counties using multiple supervised machine learning models.

Journal of environmental management
China, the world's largest carbon emitter, plays a pivotal role in achieving carbon neutrality. This study systematically analyzes the impact of landscape indices on carbon emissions from rural settlements across more than 2800 counties using eight s...

Improving groundwater quality predictions in semi-arid regions using ensemble learning models.

Environmental science and pollution research international
Groundwater resources constitute one of the primary sources of freshwater in semi-arid and arid climates. Monitoring the groundwater quality is an essential component of environmental management. In this study, a comprehensive comparison was conducte...

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...