AIMC Topic: Neural Networks, Computer

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Machine learning in Alzheimer's disease genetics.

Nature communications
Traditional statistical approaches have advanced our understanding of the genetics of complex diseases, yet are limited to linear additive models. Here we applied machine learning (ML) to genome-wide data from 41,686 individuals in the largest Europe...

Deep learning algorithm-assisted non-destructive detection of TBARS values of salmon flesh using multi-modal molecular spectra fusion.

Food chemistry
This study presents a deep learning framework for the non-destructive assessment of lipid oxidation in salmon flesh, quantified by thiobarbituric acid reactive substances (TBARS), under diverse storage conditions (-20, 0, 4, 20 °C, and dynamic temper...

Machine learning enhanced process design in protein a chromatography.

Journal of chromatography. A
Quality by Digital Design (QbDD) employs in-silico experimentation to reduce wet-lab reliance and accelerate development. Design space identification is critical for QbDD to overcome bottlenecks and streamline process design. Traditional design space...

Multi-modal emotional analysis in customer relation management and enhancing communication through integrated affective computing.

Scientific reports
An important part of customer relationship management (CRM) is being able to read emails for emotional cues; this helps with both communication and keeping customers satisfied. This study aims to improve email emotion identification by creating a sys...

Predicting wheat yield using deep learning and multi-source environmental data.

Scientific reports
Accurate forecasting of crop yields is essential for ensuring food security and promoting sustainable agricultural practices. Winter wheat, a key staple crop in Pakistan, faces challenges in yield prediction because of the complex interactions among ...

Early detection of ICU-acquired infections using high-frequency electronic health record data.

BMC medical informatics and decision making
BACKGROUND: Nosocomial infections are a major cause of morbidity and mortality in the ICU. Earlier identification of these complications may facilitate better clinical management and improve outcomes. We developed a dynamic prediction model that leve...

A deep ensemble framework for human essential gene prediction by integrating multi-omics data.

Scientific reports
Essential genes are necessary for the survival or reproduction of a living organism. The prediction and analysis of gene essentiality can advance our understanding of basic life and human diseases, and further boost the development of new drugs. We p...

MDNCT: a multi-domain neurocognitive transformer architecture approach for early prediction of autism spectrum disorders.

Scientific reports
Intellectual disability (ID) refers to a disorder involving intelligence and adaptive behavior that meets specific criteria involving deviance from the norm in terms of degree. ID is more common in males than females, and the causes can be genetic or...

A novel framework GRCornShot for corn disease detection using few shot learning with prototypical network.

Scientific reports
Precision and timeliness in the detection of plant diseases are important to limit crop losses and maintain global food security. Much work has been performed to detect plant diseases using deep learning methods. However, deep learning techniques dem...

Open-source convolutional neural network to classify distal radial fractures according to the AO/OTA classification on plain radiographs.

European journal of trauma and emergency surgery : official publication of the European Trauma Society
PURPOSE: Convolutional Neural Networks (CNNs) have shown promise in fracture detection, but their ability to improve surgeons' inconsistent fracture classification remains unstudied. Therefore, our aim was create and (externally) validate the perform...