AIMC Topic: Reproducibility of Results

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Quantitating the art and science of esthetic clinical success.

Journal of the World federation of orthodontists
BACKGROUND: Beginning with the biobehavioral bases of esthetic experiences, this article presents a quantitative analytic review of the motives and methods of providers and consumers of orthodontic treatment.

Machine learning for the prediction of pathologic pneumatosis intestinalis.

Surgery
BACKGROUND: The radiographic finding of pneumatosis intestinalis can indicate a spectrum of underlying processes ranging from a benign finding to a life-threatening condition. Although radiographic pneumatosis intestinalis is relatively common, there...

Cheetah: A Computational Toolkit for Cybergenetic Control.

ACS synthetic biology
Advances in microscopy, microfluidics, and optogenetics enable single-cell monitoring and environmental regulation and offer the means to control cellular phenotypes. The development of such systems is challenging and often results in bespoke setups ...

Hybrid Convolutional Neural Network for Localization of Epileptic Focus Based on iEEG.

Neural plasticity
Epileptic focus localization by analysing intracranial electroencephalogram (iEEG) plays a critical role in successful surgical therapy of resection of the epileptogenic lesion. However, manual analysis and classification of the iEEG signal by clinic...

Artificial intelligence in oncology: From bench to clinic.

Seminars in cancer biology
In the past few years, Artificial Intelligence (AI) techniques have been applied to almost every facet of oncology, from basic research to drug development and clinical care. In the clinical arena where AI has perhaps received the most attention, AI ...

Deep Learning-Based Ligand Design Using Shared Latent Implicit Fingerprints from Collaborative Filtering.

Journal of chemical information and modeling
In their previous work, Srinivas et al. [ 2018, 10, 56] have shown that implicit fingerprints capture ligands and proteins in a shared latent space, typically for the purposes of virtual screening with collaborative filtering models applied on known...

Deep Learning Algorithm for Automated Cardiac Murmur Detection via a Digital Stethoscope Platform.

Journal of the American Heart Association
Background Clinicians vary markedly in their ability to detect murmurs during cardiac auscultation and identify the underlying pathological features. Deep learning approaches have shown promise in medicine by transforming collected data into clinical...

A deep neural network-based approach for prediction of mutagenicity of compounds.

Environmental science and pollution research international
We are exposed to various chemical compounds present in the environment, cosmetics, and drugs almost every day. Mutagenicity is a valuable property that plays a significant role in establishing a chemical compound's safety. Exposure and handling of m...

Evaluating renal lesions using deep-learning based extension of dual-energy FoV in dual-source CT-A retrospective pilot study.

European journal of radiology
PURPOSE: Dual-source (DS) CT, dual-energy (DE) field of view (FoV) is limited to the size of the smaller detector array. The purpose was to establish a deep learning-based approach to DE extrapolation by estimating missing image data using data from ...

Semi-Automated Data Processing and Semi-Supervised Machine Learning for the Detection and Classification of Water-Column Fish Schools and Gas Seeps with a Multibeam Echosounder.

Sensors (Basel, Switzerland)
Multibeam echosounders are widely used for 3D bathymetric mapping, and increasingly for water column studies. However, they rapidly collect huge volumes of data, which poses a challenge for water column data processing that is often still manual and ...