AIMC Topic: Humans

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Assessing the Impact of Urban Environments on Mental Health and Perception Using Deep Learning: A Review and Text Mining Analysis.

Journal of urban health : bulletin of the New York Academy of Medicine
Understanding how outdoor environments affect mental health outcomes is vital in today's fast-paced and urbanized society. Recently, advancements in data-gathering technologies and deep learning have facilitated the study of the relationship between ...

An accessible deep learning tool for voxel-wise classification of brain malignancies from perfusion MRI.

Cell reports. Medicine
Noninvasive differential diagnosis of brain tumors is currently based on the assessment of magnetic resonance imaging (MRI) coupled with dynamic susceptibility contrast (DSC). However, a definitive diagnosis often requires neurosurgical interventions...

Predicting long-term progression of Alzheimer's disease using a multimodal deep learning model incorporating interaction effects.

Journal of translational medicine
BACKGROUND: Identifying individuals with mild cognitive impairment (MCI) at risk of progressing to Alzheimer's disease (AD) provides a unique opportunity for early interventions. Therefore, accurate and long-term prediction of the conversion from MCI...

Development and validation of 'Patient Optimizer' (POP) algorithms for predicting surgical risk with machine learning.

BMC medical informatics and decision making
BACKGROUND: Pre-operative risk assessment can help clinicians prepare patients for surgery, reducing the risk of perioperative complications, length of hospital stay, readmission and mortality. Further, it can facilitate collaborative decision-making...

BrainNet: a fusion assisted novel optimal framework of residual blocks and stacked autoencoders for multimodal brain tumor classification.

Scientific reports
A significant issue in computer-aided diagnosis (CAD) for medical applications is brain tumor classification. Radiologists could reliably detect tumors using machine learning algorithms without extensive surgery. However, a few important challenges a...

Digital pathology with artificial intelligence analysis provides insight to the efficacy of anti-fibrotic compounds in human 3D MASH model.

Scientific reports
Metabolic dysfunction-associated steatohepatitis (MASH) is a severe liver disease characterized by lipid accumulation, inflammation and fibrosis. The development of MASH therapies has been hindered by the lack of human translational models and limita...

Enabling large-scale screening of Barrett's esophagus using weakly supervised deep learning in histopathology.

Nature communications
Timely detection of Barrett's esophagus, the pre-malignant condition of esophageal adenocarcinoma, can improve patient survival rates. The Cytosponge-TFF3 test, a non-endoscopic minimally invasive procedure, has been used for diagnosing intestinal me...

How experienced robotic nurses adapt to the Hugo™ RAS system.

Journal of robotic surgery
No studies have reported on the impact at team level of the Medtronic Hugo RAS system. We described the work patterns and learning curves of an experienced robotic nurse team adapting to the new robotic system. We prospectively recorded the robotic n...

Effects of thienopyridine class antiplatelets on bleeding outcomes following robot-assisted radical prostatectomy.

Scientific reports
This study aimed to assess the effects of thienopyridine-class antiplatelet agents (including ticlopidine, clopidogrel, and prasugrel) on bleeding complications in patients who underwent robot-assisted radical prostatectomy. This cohort study used a ...