AIMC Topic: Machine Learning

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Accurate and efficient prediction of atmospheric PM, PM, PM, and O concentrations using a customized software package based on a machine-learning algorithm.

Chemosphere
Particulate matter (PM) and ozone (O) pollution have been attracting increasing attention recently due to their severe harm to human health. PM and O are secondary pollutants, and there remain significant challenges in accurately and efficiently pred...

Preoperative prediction of post hepatectomy liver failure after surgery for hepatocellular carcinoma on CT-scan by machine learning and radiomics analyses.

European journal of surgical oncology : the journal of the European Society of Surgical Oncology and the British Association of Surgical Oncology
INTRODUCTION: No instruments are available to predict preoperatively the risk of posthepatectomy liver failure (PHLF) in HCC patients. The aim was to predict the occurrence of PHLF preoperatively by radiomics and clinical data through machine-learnin...

Machine Learning Algorithms to Predict the Risk of Rupture of Intracranial Aneurysms: a Systematic Review.

Clinical neuroradiology
PURPOSE: Subarachnoid haemorrhage is a potentially fatal consequence of intracranial aneurysm rupture, however, it is difficult to predict if aneurysms will rupture. Prophylactic treatment of an intracranial aneurysm also involves risk, hence identif...

Identification and validation of biomarkers related to mitochondria during ex vivo lung perfusion for lung transplants based on machine learning algorithm.

Gene
BACKGROUND: Ex vivo lung perfusion (EVLP) is a critical strategy to rehabilitate marginal donor lungs, thereby increasing lung transplantation (LTx) rates. Ischemia-reperfusion (I/R) injury inevitably occurs during LTx. Exploring the common mechanism...

Exploring drug-target interaction prediction on cold-start scenarios via meta-learning-based graph transformer.

Methods (San Diego, Calif.)
Predicting drug-target interaction (DTI) is of great importance for drug discovery and development. With the rapid development of biological and chemical technologies, computational methods for DTI prediction are becoming a promising approach. Howeve...

Machine learning models for risk prediction of cancer-associated thrombosis: a systematic review and meta-analysis.

Journal of thrombosis and haemostasis : JTH
BACKGROUND: Although the number of models for predicting the risk of cancer-associated thrombosis has been rising, there is still a lack of comprehensive assessment for machine learning prediction models.

Prediction of pharmacological response in OCD using machine learning techniques and clinical and neuropsychological variables.

Spanish journal of psychiatry and mental health
INTRODUCTION: Obsessive compulsive disorder is associated with affected executive functioning, including memory, cognitive flexibility, and organizational strategies. As it was reported in previous studies, patients with preserved executive functions...

Decoding Continuous Tracking Eye Movements from Cortical Spiking Activity.

International journal of neural systems
Eye movements are the primary way primates interact with the world. Understanding how the brain controls the eyes is therefore crucial for improving human health and designing visual rehabilitation devices. However, brain activity is challenging to d...

Random Forest Prognostication of Survival and 6-Month Outcome in Pediatric Patients Following Decompressive Craniectomy for Traumatic Brain Injury.

World neurosurgery
BACKGROUND: There is a dearth of literature regarding prognostic and predictive factors for outcome following pediatric decompressive craniectomy (DC) performed after traumatic brain injury (TBI). The aim of this study was to develop a random forest ...

A Divide-and-Conquer Approach to Nanoparticle Global Optimisation Using Machine Learning.

Journal of chemical information and modeling
Global optimization of the structure of atomic nanoparticles is often hampered by the presence of many funnels on the potential energy surface. While broad funnels are readily encountered and easily exploited by the search, narrow funnels are more di...