AIMC Topic: Deep Learning

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Amplification-free detection of mycoplasma pneumoniae via CRISPR-Cas12a and deep learning-optimized crRNAs on a lateral flow platform.

Journal of pharmaceutical and biomedical analysis
Accurate and rapid diagnosis of Mycoplasma pneumoniae infection is essential for reducing its significant health burden. An amplification-free CRISPR-Cas12a-mediated detection platform has been developed, incorporating a deep learning-optimized crRNA...

TEMC-Cas: Accurate Cas Protein Classification via Combined Contrastive Learning and Protein Language Models.

ACS synthetic biology
The accurate classification of Cas proteins is crucial for understanding CRISPR-Cas systems and developing genome-editing tools. Here, we present TEMC-Cas, a deep learning framework for accurate classification of Cas proteins that combines a finely t...

A generalizable deep learning framework for structure-based protein-ligand affinity ranking.

Proceedings of the National Academy of Sciences of the United States of America
Rapid and accurate estimation of protein-ligand binding affinities is crucial for early-stage drug discovery, yet hindered by a trade-off between the accuracy of gold-standard physics-based methods and the speed of simpler empirical scoring functions...

A protein dynamics-based deep learning model enhances predictions of fitness and epistasis.

Proceedings of the National Academy of Sciences of the United States of America
Deep learning has advanced our ability to assess the effects that individual mutations have on protein function; however, predicting the complex interplay between two or more mutations remains challenging. Here, we seek to address this challenge by b...

Multi-channel deep learning radiomics model based on contrast-enhanced CT for predicting postoperative prognosis in laryngeal carcinoma.

BMC cancer
BACKGROUND: Accurate prediction of prognosis and risk stratification in patients with laryngeal cancer can inform appropriate treatment decision-making. This study aims to develop a multi-channel deep learning radiomics model based on contrast-enhanc...

An artificial neural network approach for predicting infant mortality status in Ethiopia.

BMC public health
Infant mortality is a major public health issue that is rooted in the larger problem of socio-economic and healthcare disparities. Deep learning techniques were employed in this study to predict infant mortality using data gathered via 2019 Ethiopia ...

A modified deep learning approach for seminal vesicle region localization in prostate MRI.

Scientific reports
The seminal vesicle region plays a crucial role in male reproductive health, and its accurate evaluation is essential for diagnosing infertility and carcinoma. Magnetic resonance imaging (MRI) is the primary modality for assessment; however, manual e...

Efficient fusion transformer model for accurate classification of eye diseases.

Scientific reports
The automatic diagnosis model of medical image based on deep learning can improve the diagnosis efficiency and reduce the diagnosis cost. At present, there is a lack of research on special artificial intelligence models for medical image analysis of ...

A deep learning framework for Ethiopian sign language recognition using skeleton-based representation.

Scientific reports
This study proposes an environment- and signer-invariant sign language recognition model. The model first extracts skeletal key-points from the signer via MediaPipe, which is Google's cross-platform pipeline framework that helps to detect and track h...

Enhancing explainability in epidemiological predictions using fuzzy logic integrated with machine and deep learning algorithms.

Scientific reports
Epidemiological data is often analyzed without fully accounting for the uncertainties that are key to understanding the nuances of the dataset. While traditional approaches like the SIR mathematical model provide valuable insights, our study aims to ...