AIMC Topic: Neural Networks, Computer

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Quality control system for mammographic breast positioning using deep learning.

Scientific reports
This study proposes a deep convolutional neural network (DCNN) classification for the quality control and validation of breast positioning criteria in mammography. A total of 1631 mediolateral oblique mammographic views were collected from an open da...

Genomic benchmarks: a collection of datasets for genomic sequence classification.

BMC genomic data
BACKGROUND: Recently, deep neural networks have been successfully applied in many biological fields. In 2020, a deep learning model AlphaFold won the protein folding competition with predicted structures within the error tolerance of experimental met...

Wide and deep learning based approaches for classification of Alzheimer's disease using genome-wide association studies.

PloS one
The increasing incidence of Alzheimer's disease (AD) has been leading towards a significant growth in socioeconomic challenges. A reliable prediction of AD might be useful to mitigate or at-least slow down its progression for which, identification of...

LiteGaze: Neural architecture search for efficient gaze estimation.

PloS one
Gaze estimation plays a critical role in human-centered vision applications such as human-computer interaction and virtual reality. Although significant progress has been made in automatic gaze estimation by deep convolutional neural networks, it is ...

Convolutional neural network-based evaluation of chemical maps obtained by fast Raman imaging for prediction of tablet dissolution profiles.

International journal of pharmaceutics
In this work, the capabilities of a state-of-the-art fast Raman imaging apparatus are exploited to gain information about the concentration and particle size of hydroxypropyl methylcellulose (HPMC) in sustained release tablets. The extracted informat...

Explaining and Visualizing Embeddings of One-Dimensional Convolutional Models in Human Activity Recognition Tasks.

Sensors (Basel, Switzerland)
Human Activity Recognition (HAR) is a complex problem in deep learning, and One-Dimensional Convolutional Neural Networks (1D CNNs) have emerged as a popular approach for addressing it. These networks efficiently learn features from data that can be ...

AI-Driven De Novo Design and Molecular Modeling for Discovery of Small-Molecule Compounds as Potential Drug Candidates Targeting SARS-CoV-2 Main Protease.

International journal of molecular sciences
Over the past three years, significant progress has been made in the development of novel promising drug candidates against COVID-19. However, SARS-CoV-2 mutations resulting in the emergence of new viral strains that can be resistant to the drugs use...

Deep Learning vs Traditional Models for Predicting Hospital Readmission among Patients with Diabetes.

AMIA ... Annual Symposium proceedings. AMIA Symposium
A hospital readmission risk prediction tool for patients with diabetes based on electronic health record (EHR) data is needed. The optimal modeling approach, however, is unclear. In 2,836,569 encounters of 36,641 diabetes patients, deep learning (DL)...

Progressive growing of Generative Adversarial Networks for improving data augmentation and skin cancer diagnosis.

Artificial intelligence in medicine
Early melanoma diagnosis is the most important factor in the treatment of skin cancer and can effectively reduce mortality rates. Recently, Generative Adversarial Networks have been used to augment data, prevent overfitting and improve the diagnostic...

From modern CNNs to vision transformers: Assessing the performance, robustness, and classification strategies of deep learning models in histopathology.

Medical image analysis
While machine learning is currently transforming the field of histopathology, the domain lacks a comprehensive evaluation of state-of-the-art models based on essential but complementary quality requirements beyond a mere classification accuracy. In o...