AIMC Topic: Deep Learning

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Secure facial biometric authentication in smart cities using multimodal methodology.

Scientific reports
In recent times, in modern smart city environments, securing and maintaining facial biometric security is crucial for preventing unauthorized access to citizen data and safeguarding it from spoofing. This research proposes a multimodal deep learning ...

Differences in different reconstruction algorithms for coronary CTA demonstrating pericoronary adipose tissue attenuation.

Scientific reports
The Fat Attenuation Index (FAI) surrounding the coronary arteries, a sensitive biomarker for coronary inflammation, can be measured through standard Coronary Computed Tomography Angiography (CCTA). The aim of this study is to evaluate the differences...

Automatic classification of uveal melanoma response patterns following ruthenium-106 plaque brachytherapy using ultrasound images and deep convolutional neural network.

Scientific reports
Following uveal melanoma (UM) affected treatment using ruthenium-106 brachytherapy, tumor thickness patterns fall into one of four categories: decrease (regression), increase (recurrence), stop (stable), or other, which are assessed in follow-up A-mo...

Ultrasound and SWE-based transfer learning for predicting fibrotic NASH.

Scientific reports
The aim of this study was to develop a combined deep-learning model utilizing liver ultrasound, liver elastography images, and clinical features to predict and diagnose fibrotic non-alcoholic steatohepatitis (NASH). A rat model of liver steatosis and...

AI-driven molecular modeling and design: from property prediction to drug generation.

Journal of computer-aided molecular design
Integrating the techniques of deep learning, particularly graph neural network models, has made a significant advancement in drug discovery by facilitating effective exploration of chemical spaces and precise prediction of molecular properties. This ...

SDMFFN: a novel specular detection median filtering fusion network for specular reflection removal in endoscopic images.

Biomedical physics & engineering express
. Endoscopic imaging is vital in Minimally Invasive Surgery (MIS), but its utility is often compromised by specular reflections that obscure important details and hinder diagnostic accuracy. Existing methods to address these reflections face limitati...

Prediction of urban heat island intensity based on multiple linear regression and deep learning.

PloS one
The rapid urbanization process has led to many prominent environmental issues in urban areas, resulting from a drastic change in land use. The Urban Heat Island (UHI) effect is of particular concern because it has a significant impact on the livabili...

Development of an automated ultrasonographic detection method for fecal retention using a transgluteal cleft approach.

PloS one
This study aimed to develop an artificial intelligence-based classification system using ultrasound images obtained via a transgluteal cleft scanning approach for detecting fecal retention in the lower rectum. The goal was to support accurate, object...

Reinforcement learning for medical image analysis: a systematic review of algorithms, engineering challenges, and clinical deployment.

Computer assisted surgery (Abingdon, England)
Reinforcement learning (RL) has emerged as a powerful artificial intelligence paradigm in medical image analysis, excelling in complex decision-making tasks. This systematic review synthesizes the applications of RL across diverse imaging domains-inc...

Intelligent glucose management in hospitalized patients: Short-term glucose and adverse events prediction.

PloS one
The management of blood glucose in hospitalized patients is confined to retrospective interventions, preventing healthcare professionals from predicting patients' blood glucose levels and potential adverse events in advance. This study employs a deep...