AIMC Topic: Deep Learning

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Improving Cardiology-Rehospitalization Prediction Through the Synergy of Process Mining and Deep Learning: An Innovative Approach.

Studies in health technology and informatics
Nowadays, hospitals are facing the need for an accurate prediction of rehospitalizations. Rehospitalizations, indeed, represent both a high financial burden for the hospital and a proxy measure of care quality. The current work aims to address such a...

Deep learning for precision medicine: Guiding laser therapy in ischemic retinal diseases.

Cell reports. Medicine
In this issue of Cell Reports Medicine, Zhao and colleagues report a multi-tasking artificial intelligence system that can assist the whole process of fundus fluorescein angiography (FFA) imaging and reduce the reliance on retinal specialists in FFA ...

Design and implementation of a smart Internet of Things chest pain center based on deep learning.

Mathematical biosciences and engineering : MBE
The data input process for most chest pain centers is not intelligent, requiring a lot of staff to manually input patient information. This leads to problems such as long processing times, high potential for errors, an inability to access patient dat...

Combination of deep learning and 2D CARS figures for identification of amyloid-β plaques.

Optics express
In vivo imaging and accurate identification of amyloid-β (Aβ) plaque are crucial in Alzheimer's disease (AD) research. In this work, we propose to combine the coherent anti-Stokes Raman scattering (CARS) microscopy, a powerful detection technology fo...

Improving the Accuracy and Speed of Visual Field Testing in Glaucoma With Structural Information and Deep Learning.

Translational vision science & technology
PURPOSE: To assess the performance of a perimetric strategy using structure-function predictions from a deep learning (DL) model.

DeepCCI: a deep learning framework for identifying cell-cell interactions from single-cell RNA sequencing data.

Bioinformatics (Oxford, England)
MOTIVATION: Cell-cell interactions (CCIs) play critical roles in many biological processes such as cellular differentiation, tissue homeostasis, and immune response. With the rapid development of high throughput single-cell RNA sequencing (scRNA-seq)...

Development and Validation of a Deep Learning-Based Histologic Diagnosis System for Diagnosing Colorectal Sessile Serrated Lesions.

American journal of clinical pathology
OBJECTIVES: The histopathologic diagnosis of colorectal sessile serrated lesions (SSLs) and hyperplastic polyps (HPs) is of low consistency among pathologists. This study aimed to develop and validate a deep learning (DL)-based logical anthropomorphi...

Deep Learning for Automated Triaging of Stable Chest Radiographs in a Follow-up Setting.

Radiology
Background Most artificial intelligence algorithms that interpret chest radiographs are restricted to an image from a single time point. However, in clinical practice, multiple radiographs are used for longitudinal follow-up, especially in intensive ...

ExpertNet: A Deep Learning Approach to Combined Risk Modeling and Subtyping in Intensive Care Units.

IEEE journal of biomedical and health informatics
Risk models play a crucial role in disease prevention, particularly in intensive care units (ICUs). Diseases often have complex manifestations with heterogeneous subpopulations, or subtypes, that exhibit distinct clinical characteristics. Risk models...

Deep learning to predict esophageal variceal bleeding based on endoscopic images.

The Journal of international medical research
OBJECTIVE: Esophageal varix (EV) bleeding is a particularly serious complications of cirrhosis. Prediction of EV bleeding requires extensive endoscopy experience; it remains unreliable and inefficient. This retrospective cohort study evaluated the fe...