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Toward a Vision-Based Intelligent System: A Stacked Encoded Deep Learning Framework for Sign Language Recognition.

Publication Type: Academic Journal

Source(s): Sensors (Basel, Switzerland) [Sensors (Basel)] 2023 Nov 09; Vol. 23 (22). Date of Electronic Publication: 2023 Nov 09.

Abstract: Sign language recognition, an essential interface between the hearing and deaf-mute communities, faces challenges with high false positive rates and computational costs, even with the use of advanced deep learning techniques. Our proposed solution is a...

Hybrid deep learning approach to improve classification of low-volume high-dimensional data.

Publication Type: Academic Journal

Source(s): BMC bioinformatics [BMC Bioinformatics] 2023 Nov 07; Vol. 24 (1), pp. 419. Date of Electronic Publication: 2023 Nov 07.

Abstract: Background: The performance of machine learning classification methods relies heavily on the choice of features. In many domains, feature generation can be labor-intensive and require domain knowledge, and feature selection methods do not scale well in...

Deep Learning for Epidemiologists: An Introduction to Neural Networks.

Publication Type: Academic Journal

Source(s): American journal of epidemiology [Am J Epidemiol] 2023 Nov 03; Vol. 192 (11), pp. 1904-1916.

Authors:

Abstract: Deep learning methods are increasingly being applied to problems in medicine and health care. However, few epidemiologists have received formal training in these methods. To bridge this gap, this article introduces the fundamentals of deep learning fro...

Applications of machine learning and deep learning in SPECT and PET imaging: General overview, challenges and future prospects.

Publication Type: Academic Journal

Source(s): Pharmacological research [Pharmacol Res] 2023 Nov; Vol. 197, pp. 106984. Date of Electronic Publication: 2023 Nov 07.

Abstract: The integration of positron emission tomography (PET) and single-photon emission computed tomography (SPECT) imaging techniques with machine learning (ML) algorithms, including deep learning (DL) models, is a promising approach. This integration enhanc...

Noise2Recon: Enabling SNR-robust MRI reconstruction with semi-supervised and self-supervised learning.

Publication Type: Academic Journal

Source(s): Magnetic resonance in medicine [Magn Reson Med] 2023 Nov; Vol. 90 (5), pp. 2052-2070. Date of Electronic Publication: 2023 Jul 10.

Abstract: Purpose: To develop a method for building MRI reconstruction neural networks robust to changes in signal-to-noise ratio (SNR) and trainable with a limited number of fully sampled scans.Methods: We propose Noise2Recon, a consistency training method for ...

On-Device Execution of Deep Learning Models on HoloLens2 for Real-Time Augmented Reality Medical Applications.

Publication Type: Academic Journal

Source(s): Sensors (Basel, Switzerland) [Sensors (Basel)] 2023 Oct 25; Vol. 23 (21). Date of Electronic Publication: 2023 Oct 25.

Abstract: The integration of Deep Learning (DL) models with the HoloLens2 Augmented Reality (AR) headset has enormous potential for real-time AR medical applications. Currently, most applications execute the models on an external server that communicates with th...

An effective correlation-based data modeling framework for automatic diabetes prediction using machine and deep learning techniques.

Publication Type: Academic Journal

Source(s): BMC bioinformatics [BMC Bioinformatics] 2023 Oct 02; Vol. 24 (1), pp. 372. Date of Electronic Publication: 2023 Oct 02.

Abstract: The rising risk of diabetes, particularly in emerging countries, highlights the importance of early detection. Manual prediction can be a challenging task, leading to the need for automatic approaches. The major challenge with biomedical datasets is da...

Recent advancements in machine learning and deep learning-based breast cancer detection using mammograms.

Publication Type: Academic Journal

Source(s): Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB) [Phys Med] 2023 Oct; Vol. 114, pp. 103138. Date of Electronic Publication: 2023 Sep 28.

Authors:

Abstract: Objective: Mammogram-based automatic breast cancer detection has a primary role in accurate cancer diagnosis and treatment planning to save valuable lives. Mammography is one basic yet efficient test for screening breast cancer. Very few comprehensive ...

Artificial intelligence, machine learning and deep learning: Potential resources for the infection clinician.

Publication Type: Academic Journal

Source(s): The Journal of infection [J Infect] 2023 Oct; Vol. 87 (4), pp. 287-294. Date of Electronic Publication: 2023 Jul 17.

Abstract: Background: Artificial intelligence (AI), machine learning and deep learning (including generative AI) are increasingly being investigated in the context of research and management of human infection.Objectives: We summarise recent and potential future...

A systematic review on intracranial aneurysm and hemorrhage detection using machine learning and deep learning techniques.

Publication Type: Academic Journal

Source(s): Progress in biophysics and molecular biology [Prog Biophys Mol Biol] 2023 Oct; Vol. 183, pp. 1-16. Date of Electronic Publication: 2023 Jul 25.

Abstract: The risk of discovering an intracranial aneurysm during the initial screening and follow-up screening are reported as around 11%, and 7% respectively (Zuurbie et al., 2023) to these mass effects, unruptured aneurysms frequently generate symptoms, howev...

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