AIMC Topic: Neural Networks, Computer

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Targeted design of synthetic enhancers for selected tissues in the Drosophila embryo.

Nature
Enhancers control gene expression and have crucial roles in development and homeostasis. However, the targeted de novo design of enhancers with tissue-specific activities has remained challenging. Here we combine deep learning and transfer learning t...

Three-dimensional spine reconstruction from biplane radiographs using convolutional neural networks.

Medical engineering & physics
PURPOSE: The purpose of this study was to develop and evaluate a deep learning network for three-dimensional reconstruction of the spine from biplanar radiographs.

Prediction of brain sex from EEG: using large-scale heterogeneous dataset for developing a highly accurate and interpretable ML model.

NeuroImage
This study presents a comprehensive examination of sex-related differences in resting-state electroencephalogram (EEG) data, leveraging two different types of machine learning models to predict an individual's sex. We utilized data from the Two Decad...

Application of Artificial Intelligence or machine learning in risk sharing agreements for pharmacotherapy risk management.

Journal of integrative bioinformatics
Applications of Artificial Intelligence in medical informatics solutions risk sharing have social value. At a time of ever-increasing cost for the provision of medicines to citizens, there is a need to restrain the growth of health care costs. The se...

Retinal Photograph-based Deep Learning System for Detection of Thyroid-Associated Ophthalmopathy.

The Journal of craniofacial surgery
BACKGROUND: The diagnosis of thyroid-associated ophthalmopathy (TAO) usually requires a comprehensive examination, including clinical symptoms, radiological examinations, and blood tests. Therefore, cost-effective and noninvasive methods for the dete...

Optimizing dense feed-forward neural networks.

Neural networks : the official journal of the International Neural Network Society
Deep learning models have been widely used during the last decade due to their outstanding learning and abstraction capacities. However, one of the main challenges any scientist has to face using deep learning models is to establish the network's arc...

U-Net-Based Assistive Identification of Bladder Cancer: A Promising Approach for Improved Diagnosis.

Urologia internationalis
INTRODUCTION: Bladder cancer (BC) is a major health concern that poses a significant threat to the population, with an increasing incidence rate and a high risk of recurrence and progression. The primary clinical method for diagnosing BC is cystoscop...

Time series-based hybrid ensemble learning model with multivariate multidimensional feature coding for DNA methylation prediction.

BMC genomics
BACKGROUND: DNA methylation is a form of epigenetic modification that impacts gene expression without modifying the DNA sequence, thereby exerting control over gene function and cellular development. The prediction of DNA methylation is vital for und...

A thermodynamical model of non-deterministic computation in cortical neural networks.

Physical biology
Neuronal populations in the cerebral cortex engage in probabilistic coding, effectively encoding the state of the surrounding environment with high accuracy and extraordinary energy efficiency. A new approach models the inherently probabilistic natur...