AIMC Topic: Neural Networks, Computer

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CPred: Charge State Prediction for Modified and Unmodified Peptides in Electrospray Ionization.

Analytical chemistry
The mass-to-charge ratio serves as a critical parameter in peptide identification via mass spectrometry, enabling the precise determination of peptide masses and facilitating their differentiation based on unique charge characteristics, especially wh...

Liver Cancer Diagnosis: Enhanced Deep Maxout Model with Improved Feature Set.

Cancer investigation
This work proposed a liver cancer classification scheme that includes Preprocessing, Feature extraction, and classification stages. The source images are pre-processed using Gaussian filtering. For segmentation, this work proposes a LUV transformatio...

Deep Learning-Based System Combining Chest X-Ray and Computerized Tomography Images for COVID-19 Diagnosis.

British journal of hospital medicine (London, England : 2005)
The coronavirus disease 2019 (COVID-19) pandemic has highlighted the need for accurate and efficient diagnostic methods. This study aims to improve COVID-19 detection by integrating chest X-ray (CXR) and computerized tomography (CT) images using dee...

A Point Cloud Graph Neural Network for Protein-Ligand Binding Site Prediction.

International journal of molecular sciences
Predicting protein-ligand binding sites is an integral part of structural biology and drug design. A comprehensive understanding of these binding sites is essential for advancing drug innovation, elucidating mechanisms of biological function, and exp...

Neural shape completion for personalized Maxillofacial surgery.

Scientific reports
In this paper, we investigate the effectiveness of shape completion neural networks as clinical aids in maxillofacial surgery planning. We present a pipeline to apply shape completion networks to automatically reconstruct complete eumorphic 3D meshes...

An end-to-end framework for the prediction of protein structure and fitness from single sequence.

Nature communications
Significant research progress has been made in the field of protein structure and fitness prediction. Particularly, single-sequence-based structure prediction methods like ESMFold and OmegaFold achieve a balance between inference speed and prediction...

Classification of optic neuritis in neuromyelitis optica spectrum disorders (NMOSD) on MRI using CNN with transfer learning and manipulation of pre-processing on augmentation.

Biomedical physics & engineering express
Neuromyelitis optica spectrum disorder (NMOSD), also known as Devic disease, is an autoimmune central nervous system disorder in humans that commonly causes inflammatory demyelination in the optic nerves and spinal cord. Inflammation in the optic ner...

A new method of rock type identification based on transformer by utilizing acoustic emission.

PloS one
The characterization and analysis of rock types based on acoustic emission (AE) signals have long been focal points in earth science research. However, traditional analysis methods struggle to handle the influx of big data. While signal processing me...

Automated brain tumor diagnostics: Empowering neuro-oncology with deep learning-based MRI image analysis.

PloS one
Brain tumors, characterized by the uncontrolled growth of abnormal cells, pose a significant threat to human health. Early detection is crucial for successful treatment and improved patient outcomes. Magnetic Resonance Imaging (MRI) is the primary di...

Artificial neural network prediction of postoperative complications in papillary thyroid microcarcinoma based on preoperative ultrasonographic features.

Journal of clinical ultrasound : JCU
OBJECTIVE: To predict post-thyroidectomy complications in papillary thyroid microcarcinoma (PTMC) patients using a deep learning model based on preoperative ultrasonographic features. This study addresses the global rise in PTMC incidence and the cha...