AIMC Topic: Deep Learning

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Deep Learning-reconstructed Parallel Accelerated Imaging for Knee MRI.

Current medical imaging
BACKGROUND: Deep learning (DL) can improve image quality by removing noise from accelerated MRI.

Classification of Brain Tumours in MRI Images using a Convolutional Neural Network.

Current medical imaging
INTRODUCTION: Recent advances in deep learning have aided the well-being business in Medical Imaging of numerous disorders like brain tumours, a serious malignancy caused by unregulated and aberrant cell portioning. The most frequent and widely used ...

Deep Learning from Phylogenies for Diversification Analyses.

Systematic biology
Birth-death (BD) models are widely used in combination with species phylogenies to study past diversification dynamics. Current inference approaches typically rely on likelihood-based methods. These methods are not generalizable, as a new likelihood ...

Optimizing platelet transfusion through a personalized deep learning risk assessment system for demand management.

Blood
Platelet demand management (PDM) is a resource-consuming task for physicians and transfusion managers of large hospitals. Inpatient numbers and institutional standards play significant roles in PDM. However, reliance on these factors alone commonly r...

ChatGPT-assisted deep learning model for thyroid nodule analysis: beyond artifical intelligence.

Medical ultrasonography
AIMS: To develop a deep learning model, with the aid of ChatGPT, for thyroid nodules, utilizing ultrasound images. The cytopathology of the fine needle aspiration biopsy (FNAB) serves as the baseline.

Pivotal trial of a deep-learning-based retinal biomarker (Reti-CVD) in the prediction of cardiovascular disease: data from CMERC-HI.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: The potential of using retinal images as a biomarker of cardiovascular disease (CVD) risk has gained significant attention, but regulatory approval of such artificial intelligence (AI) algorithms is lacking. In this regulated pivotal trial...

Active Predictive Coding: A Unifying Neural Model for Active Perception, Compositional Learning, and Hierarchical Planning.

Neural computation
There is growing interest in predictive coding as a model of how the brain learns through predictions and prediction errors. Predictive coding models have traditionally focused on sensory coding and perception. Here we introduce active predictive cod...