AIMC Topic: Algorithms

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Strategy to implement a convolutional neural network based ideal model observer via transfer learning for multi-slice simulated breast CT images.

Physics in medicine and biology
In this work, we propose a convolutional neural network (CNN)-based multi-slice ideal model observer using transfer learning (TL-CNN) to reduce the required number of training samples.To train model observers, we generate simulated breast CT image vo...

Cross-camera Performance of Deep Learning Algorithms to Diagnose Common Ophthalmic Diseases: A Comparative Study Highlighting Feasibility to Portable Fundus Camera Use.

Current eye research
PURPOSE: To compare the inter-camera performance and consistency of various deep learning (DL) diagnostic algorithms applied to fundus images taken from desktop Topcon and portable Optain cameras.

Bridging adaptive management and reinforcement learning for more robust decisions.

Philosophical transactions of the Royal Society of London. Series B, Biological sciences
From out-competing grandmasters in chess to informing high-stakes healthcare decisions, emerging methods from artificial intelligence are increasingly capable of making complex and strategic decisions in diverse, high-dimensional and uncertain situat...

Adaptive Optimal Control of Hybrid Electric Vehicle Power Battery via Policy Learning.

Computational intelligence and neuroscience
An online policy learning algorithm is used to solve the optimal control problem of the power battery state of charge (SOC) observer for the first time. The design of adaptive neural network (NN) optimal control is studied for the nonlinear power bat...

Automatic detection of Parkinson's disease from power spectral density of electroencephalography (EEG) signals using deep learning model.

Physical and engineering sciences in medicine
Parkinson's disease (PD) is characterized by slowed movements, speech disorders, an inability to control muscle movements, and tremors in the hands and feet. In the early stages of PD, the changes in these motor signs are very vague, so an objective ...

Damage Detection and Localization of Bridge Deck Pavement Based on Deep Learning.

Sensors (Basel, Switzerland)
Bridge deck pavement damage has a significant effect on the driving safety and long-term durability of bridges. To achieve the damage detection and localization of bridge deck pavement, a three-stage detection method based on the you-only-look-once v...

A CMOS Temperature Sensor with a Smart Calibrated Inaccuracy of ±0.11 (3σ).

Sensors (Basel, Switzerland)
This paper presents a BJT-based smart CMOS temperature sensor. The analog front-end circuit contains a bias circuit and a bipolar core; the data conversion interface features an incremental delta-sigma analog-to-digital converter. The circuit utilize...

Artificial intelligence applications in brachytherapy: A literature review.

Brachytherapy
PURPOSE: Artificial intelligence (AI) has the potential to simplify and optimize various steps of the brachytherapy workflow, and this literature review aims to provide an overview of the work done in this field.

Prediction of Anemia From Cerebral Venous Sinus Attenuation on Deep-Learning Reconstructed Brain Computed Tomography Images.

Journal of computer assisted tomography
OBJECTIVE: The aim of the study is to evaluate whether the prediction of anemia is possible using quantitative analyses of unenhanced cranial computed tomography (CT) with deep learning reconstruction (DLR) compared with conventional methods.

Machine learning-based drug design for identification of thymidylate kinase inhibitors as a potential anti-Mycobacterium tuberculosis.

Journal of biomolecular structure & dynamics
The rise of antibiotic-resistant Mycobacterium tuberculosis (Mtb) has reduced the availability of medications for tuberculosis therapy, resulting in increased morbidity and mortality globally. Tuberculosis spreads from the lungs to other parts of the...