AIMC Topic: Humans

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Leveraging deep learning models to understand the daily experience of anxiety in teenagers over the course of a year.

Journal of affective disorders
INTRODUCTION: Anxiety disorders are a prevalent and severe problem that are often developed early in life and can disrupt the daily lives of affected individuals for many years into adulthood. Given the persistent negative aspects of anxiety, accurat...

Artificial scaffolding: Augmenting social cognition by means of robot technology.

Autism research : official journal of the International Society for Autism Research
The concept of scaffolding refers to the support that the environment provides in the acquisition and consolidation of new abilities. Technological advancements allow for support in the acquisition of cognitive capabilities, such as second language a...

Deep learning image reconstruction algorithm: impact on image quality in coronary computed tomography angiography.

La Radiologia medica
PURPOSE: To perform a comprehensive intraindividual objective and subjective image quality evaluation of coronary CT angiography (CCTA) reconstructed with deep learning image reconstruction (DLIR) and to assess correlation with routinely applied hybr...

Initial experience of robot-assisted partial nephrectomy with Hugo™ RAS system: implications for surgical setting.

World journal of urology
PURPOSE: Hugo™ RAS system is one of the most promising new robotic platforms introduced in the field of urology. To date, no data have been provided on robot-assisted partial nephrectomy (RAPN) performed with Hugo™ RAS system. The aim of the study is...

Techniques and outcomes of robot-assisted partial nephrectomy for the treatment of multiple ipsilateral renal masses.

Minerva urology and nephrology
BACKGROUND: Patients with multiple ipsilateral renal masses have an augmented risk of metachronous contralateral lesions and are likely to undergo repeated surgeries. We report our experience with the technologies currently available and the surgical...

Automatic placental and fetal volume estimation by a convolutional neural network.

Placenta
INTRODUCTION: We aimed to develop an artificial intelligence (AI) deep learning algorithm to efficiently estimate placental and fetal volumes from magnetic resonance (MR) scans.

An approach combining deep learning and molecule docking for drug discovery of cathepsin L.

Expert opinion on drug discovery
OBJECTIVES: Cathepsin L (CTSL) is a promising therapeutic target for metabolic disorders and COVID-19. However, there are still no clinically available CTSL inhibitors. Our objective is to develop an approach for the discovery of potential reversible...

Open vs robotic intracorporeal Padua ileal bladder: functional outcomes of a single-centre RCT.

World journal of urology
PURPOSE: Functional outcomes of robot-assisted (RA) radical cystectomy (RC) with intracorporeal orthotopic neobladder (i-ON) have been poorly investigated. The study aimed to report functional outcomes of a prospective randomized controlled trial (RC...

A Methodology for Training Toolkits Implementation in Smart Labs.

Sensors (Basel, Switzerland)
Globally, educational institutes are trying to adapt modernized and effective approaches and tools to their education systems to improve the quality of their performance and achievements. However, identifying, designing, and/or developing promising m...

Putting the Personalized Metabolic Avatar into Production: A Comparison between Deep-Learning and Statistical Models for Weight Prediction.

Nutrients
Nutrition is a cross-cutting sector in medicine, with a huge impact on health, from cardiovascular disease to cancer. Employment of digital medicine in nutrition relies on digital twins: digital replicas of human physiology representing an emergent s...