AIMC Topic: Machine Learning

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Approaching coupled cluster accuracy with a general-purpose neural network potential through transfer learning.

Nature communications
Computational modeling of chemical and biological systems at atomic resolution is a crucial tool in the chemist's toolset. The use of computer simulations requires a balance between cost and accuracy: quantum-mechanical methods provide high accuracy ...

Automatic evaluation of fetal head biometry from ultrasound images using machine learning.

Physiological measurement
OBJECTIVE: Ultrasound-based fetal biometric measurements, such as head circumference (HC) and biparietal diameter (BPD), are frequently used to evaluate gestational age and diagnose fetal central nervous system pathology. Because manual measurements ...

A feature agnostic approach for glaucoma detection in OCT volumes.

PloS one
Optical coherence tomography (OCT) based measurements of retinal layer thickness, such as the retinal nerve fibre layer (RNFL) and the ganglion cell with inner plexiform layer (GCIPL) are commonly employed for the diagnosis and monitoring of glaucoma...

Machine learning to predict microbial community functions: An analysis of dissolved organic carbon from litter decomposition.

PloS one
Microbial communities are ubiquitous and often influence macroscopic properties of the ecosystems they inhabit. However, deciphering the functional relationship between specific microbes and ecosystem properties is an ongoing challenge owing to the c...

SmartPulse, a machine learning approach for calibration-free dynamic RF shimming: Preliminary study in a clinical environment.

Magnetic resonance in medicine
PURPOSE: A calibration-free pulse design method is introduced to alleviate artifacts in clinical routine with parallel transmission at high field, dealing with significant inter-subject variability, found for instance in the abdomen.

A Ligand-Based Virtual Screening Method Using Direct Quantification of Generalization Ability.

Molecules (Basel, Switzerland)
Machine learning plays an important role in ligand-based virtual screening. However, conventional machine learning approaches tend to be inefficient when dealing with such problems where the data are imbalanced and features describing the chemical ch...

Automatic recognition of different types of acute leukaemia in peripheral blood by image analysis.

Journal of clinical pathology
AIMS: Morphological differentiation among different blast cell lineages is a difficult task and there is a lack of automated analysers able to recognise these abnormal cells. This study aims to develop a machine learning approach to predict the diagn...

Utilization of Artificial Intelligence in Echocardiography.

Circulation journal : official journal of the Japanese Circulation Society
Echocardiography has a central role in the diagnosis and management of cardiovascular disease. Precise and reliable echocardiographic assessment is required for clinical decision-making. Even if the development of new technologies (3-dimentional echo...

Transfusion after total knee arthroplasty can be predicted using the machine learning algorithm.

Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA
PURPOSE: A blood transfusion after total knee arthroplasty (TKA) is associated with an increase in complication and infection rates. However, no studies have been conducted to predict transfusion after TKA using a machine learning algorithm. The purp...