AIMC Topic: Humans

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HSM6AP: a high-precision predictor for the Homo N6-methyladenosine (m^6 A) based on multiple weights and feature stitching.

RNA biology
Recent studies have shown that RNA methylation modification can affect RNA transcription, metabolism, splicing and stability. In addition, RNA methylation modification has been associated with cancer, obesity and other diseases. Based on information ...

Artificial intelligence, machine learning, and drug repurposing in cancer.

Expert opinion on drug discovery
: Drug repurposing provides a cost-effective strategy to re-use approved drugs for new medical indications. Several machine learning (ML) and artificial intelligence (AI) approaches have been developed for systematic identification of drug repurposin...

Novel deep learning-based noise reduction technique for prostate magnetic resonance imaging.

Abdominal radiology (New York)
INTRODUCTION: Magnetic resonance imaging (MRI) has played an increasingly major role in the evaluation of patients with prostate cancer, although prostate MRI presents several technical challenges. Newer techniques, such as deep learning (DL), have b...

Paradoxical sensory reactivity induced by functional disconnection in a robot model of neurodevelopmental disorder.

Neural networks : the official journal of the International Neural Network Society
Neurodevelopmental disorders are characterized by heterogeneous and non-specific nature of their clinical symptoms. In particular, hyper- and hypo-reactivity to sensory stimuli are diagnostic features of autism spectrum disorder and are reported acro...

Automatic screening of tear meniscus from lacrimal duct obstructions using anterior segment optical coherence tomography images by deep learning.

Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie
PURPOSE: We assessed the ability of deep learning (DL) models to distinguish between tear meniscus of lacrimal duct obstruction (LDO) patients and normal subjects using anterior segment optical coherence tomography (ASOCT) images.

Machine learning algorithms trained with pre-hospital acquired history-taking data can accurately differentiate diagnoses in patients with hip complaints.

Acta orthopaedica
Background and purpose - Machine learning (ML) techniques are a form of artificial intelligence able to analyze big data. Analyzing the outcome of (digital) questionnaires, ML might recognize different patterns in answers that might relate to differe...

DeepHCS: Bright-field to fluorescence microscopy image conversion using multi-task learning with adversarial losses for label-free high-content screening.

Medical image analysis
In this paper, we propose a novel microscopy image translation method for transforming a bright-field microscopy image into three different fluorescence images to observe the apoptosis, nuclei, and cytoplasm of cells, which visualize dead cells, nucl...

Automated Vision-Based Microsurgical Skill Analysis in Neurosurgery Using Deep Learning: Development and Preclinical Validation.

World neurosurgery
BACKGROUND/OBJECTIVE: Technical skill acquisition is an essential component of neurosurgical training. Educational theory suggests that optimal learning and improvement in performance depends on the provision of objective feedback. Therefore, the aim...

Functional annotation of human cognitive states using deep graph convolution.

NeuroImage
A key goal in neuroscience is to understand brain mechanisms of cognitive functions. An emerging approach is "brain decoding", which consists of inferring a set of experimental conditions performed by a participant, using pattern classification of br...

Leveraging innovative technology to generate drug response phenotypes for the advancement of biomarker-driven precision dosing.

Clinical and translational science
Although traditional approaches to biomarker discovery have elucidated key molecular markers that have improved drug selection (precision medicine), the discovery of biomarkers that inform optimal dose selection (precision dosing) continues to be a c...