AIMC Topic: Humans

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Revisiting the video deficit in technology-saturated environments: Successful imitation from people, screens, and social robots.

Journal of experimental child psychology
The "video deficit" is a well-documented effect whereby children learn less well about information delivered via a screen than the same information delivered in person. Research suggests that increasing social contingency may ameliorate this video de...

Bifunctional robots inducing targeted protein degradation.

European journal of medicinal chemistry
The gaining importance of Targeted Protein Degradation (TPD) and PROTACs (PROteolysis-TArgeting Chimeras) have drawn the scientific community's attention. PROTACs are considered bifunctional robots owing to their avidity for the protein of interest (...

A Deep Learning-Based System Trained for Gastrointestinal Stromal Tumor Screening Can Identify Multiple Types of Soft Tissue Tumors.

The American journal of pathology
The accuracy and timeliness of the pathologic diagnosis of soft tissue tumors (STTs) critically affect treatment decision and patient prognosis. Thus, it is crucial to make a preliminary judgement on whether the tumor is benign or malignant with hema...

Behind the ChatGPT Hype: Are Its Suggestions Contributing to Addiction?

Annals of biomedical engineering
ChatGPT has been a frequent topic of discussion lately. All over the Internet, from YouTube to blogs, there have been reports about how ChatGPT is able to plan people's daily activities, even for a whole month. However, what matters is what activitie...

Brain Tumor Classification Using Deep Neural Network and Transfer Learning.

Brain topography
In the field of medical imaging, the classification of brain tumors based on histopathological analysis is a laborious and traditional approach. To address this issue, the use of deep learning techniques, specifically Convolutional Neural Networks (C...

Diagnostic Test Accuracy of Artificial Intelligence in Detecting Periapical Periodontitis on Two-Dimensional Radiographs: A Retrospective Study and Literature Review.

Medicina (Kaunas, Lithuania)
This study aims to evaluate the diagnostic accuracy of artificial intelligence in detecting apical pathosis on periapical radiographs. A total of twenty anonymized periapical radiographs were retrieved from the database of Poznan University of Medica...

Usefulness of machine learning softwares to screen titles of systematic reviews: a methodological study.

Systematic reviews
OBJECTIVE: To investigate the usefulness and performance metrics of three freely-available softwares (Rayyan®, Abstrackr® and Colandr®) for title screening in systematic reviews.

Oncocytic adrenocortical neoplasm of borderline uncertain malignant potential diagnosed after robot-assisted adrenalectomy case report.

BMC urology
BACKGROUND: Adrenal incidentalomas are radiologically discovered tumors that represent a variety of pathologies, with the diagnosis clinched only on surgical pathology. These tumors may be clinically monitored, but triggers for surgery include size >...

Image preprocessing with contrast-limited adaptive histogram equalization improves the segmentation performance of deep learning for the articular disk of the temporomandibular joint on magnetic resonance images.

Oral surgery, oral medicine, oral pathology and oral radiology
OBJECTIVES: The objective was to evaluate the robustness of deep learning (DL)-based encoder-decoder convolutional neural networks (ED-CNNs) for segmenting temporomandibular joint (TMJ) articular disks using data sets acquired from 2 different 3.0-T ...

Data-efficient resting-state functional magnetic resonance imaging brain mapping with deep learning.

Journal of neurosurgery
OBJECTIVE: Resting-state functional MRI (RS-fMRI) enables the mapping of function within the brain and is emerging as an efficient tool for the presurgical evaluation of eloquent cortex. Models capable of reliable and precise mapping of resting-state...