AIMC Topic: Humans

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Integrative learning for population of dynamic networks with covariates.

NeuroImage
Although there is a rapidly growing literature on dynamic connectivity methods, the primary focus has been on separate network estimation for each individual, which fails to leverage common patterns of information. We propose novel graph-theoretic ap...

Experimental evaluation of deep learning method in reticulocyte enumeration in peripheral blood.

International journal of laboratory hematology
INTRODUCTION: Reticulocytes (RET) are immature red blood cells, and RET enumeration in peripheral blood has important clinical value in diagnosis, treatment efficacy observation, and prognosis of anemic diseases. For RET enumeration, flow cytometric ...

Radiomics and deep learning methods in expanding the use of screening breast MRI.

European radiology
• The use of screening breast MRI is expanding beyond high-risk women to include intermediate- and average-risk women.• The study by Pötsch et al uses a radiomics-based method to decrease the number of benign biopsies while maintaining high sensitivi...

Artificial intelligence in urological oncology: An update and future applications.

Urologic oncology
There continues to be rapid developments and research in the field of Artificial Intelligence (AI) in Urological Oncology worldwide. In this review we discuss the basics of AI, application of AI per tumour group (Renal, Prostate and Bladder Cancer) a...

Benchmarking deep learning splice prediction tools using functional splice assays.

Human mutation
Hereditary disorders are frequently caused by genetic variants that affect pre-messenger RNA splicing. Though genetic variants in the canonical splice motifs are almost always disrupting splicing, the pathogenicity of variants in the noncanonical spl...

Robotic total pelvic exenteration - a video vignette.

Colorectal disease : the official journal of the Association of Coloproctology of Great Britain and Ireland

Aesthetic preference for art can be predicted from a mixture of low- and high-level visual features.

Nature human behaviour
It is an open question whether preferences for visual art can be lawfully predicted from the basic constituent elements of a visual image. Here, we developed and tested a computational framework to investigate how aesthetic values are formed. We show...

Ligand-Dependent Conformational Transitions in Molecular Dynamics Trajectories of GPCRs Revealed by a New Machine Learning Rare Event Detection Protocol.

Molecules (Basel, Switzerland)
Central among the tools and approaches used for ligand discovery and design are Molecular Dynamics (MD) simulations, which follow the dynamic changes in molecular structure in response to the environmental condition, interactions with other proteins,...

Device-Free Human Activity Recognition with Low-Resolution Infrared Array Sensor Using Long Short-Term Memory Neural Network.

Sensors (Basel, Switzerland)
Sensor-based human activity recognition (HAR) has attracted enormous interests due to its wide applications in the Internet of Things (IoT), smart homes and healthcare. In this paper, a low-resolution infrared array sensor-based HAR approach is propo...