AIMC Topic: Machine Learning

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A machine learning model to classify aortic dissection patients in the early diagnosis phase.

Scientific reports
Aortic dissection is one of the most clinical-challenging and life-threatening cardiovascular diseases associated with high morbidity and mortality. Aortic dissection requires fast diagnosis and timely therapy. Any delay or misdiagnosis can cause sev...

Benchmarking machine learning methods for comprehensive chemical fingerprinting and pattern recognition.

Journal of chromatography. A
Machine learning (ML) has been used previously to recognize particular patterns of constituent compounds. Here, ML is used with comprehensive chemical fingerprints that capture the distribution of all constituent compounds to flexibly perform various...

Machine Learning Accurately Predicts Short-Term Outcomes Following Open Reduction and Internal Fixation of Ankle Fractures.

The Journal of foot and ankle surgery : official publication of the American College of Foot and Ankle Surgeons
Ankle fractures are common orthopedic injuries with favorable outcomes when managed with open reduction and internal fixation (ORIF). Several patient-related risk factors may contribute to poor short-term outcomes, and machine learning may be a valua...

Machine learning in whole-body MRI: experiences and challenges from an applied study using multicentre data.

Clinical radiology
Machine learning is now being increasingly employed in radiology to assist with tasks such as automatic lesion detection, segmentation, and characterisation. We are currently involved in an National Institute of Health Research (NIHR)-funded project,...

Towards end-to-end likelihood-free inference with convolutional neural networks.

The British journal of mathematical and statistical psychology
Complex simulator-based models with non-standard sampling distributions require sophisticated design choices for reliable approximate parameter inference. We introduce a fast, end-to-end approach for approximate Bayesian computation (ABC) based on fu...

Upper limb motor pre-clinical assessment in Parkinson's disease using machine learning.

Parkinsonism & related disorders
INTRODUCTION: Parkinson's disease (PD) is a common neurodegenerative disorder characterized by disabling motor and non-motor symptoms. For example, idiopathic hyposmia (IH), which is a reduced olfactory sensitivity, is typical in >95% of PD patients ...

Modelling PTSD diagnosis using sleep, memory, and adrenergic metabolites: An exploratory machine-learning study.

Human psychopharmacology
OBJECTIVE: Features of posttraumatic stress disorder (PTSD) typically include sleep disturbances, impaired declarative memory, and hyperarousal. This study evaluated whether these combined features may accurately delineate pathophysiological changes ...

IMACEL: A cloud-based bioimage analysis platform for morphological analysis and image classification.

PloS one
Automated quantitative image analysis is essential for all fields of life science research. Although several software programs and algorithms have been developed for bioimage processing, an advanced knowledge of image processing techniques and high-p...