The 2022 ieee Conference on computationalintelligence in bioinformatics and computationalbiology (ieee CIBCB 2022) was held from August 15th-17th in Ottawa, Canada. This conference has been held annually since 2004....
The 2022 ieee Conference on computationalintelligence in bioinformatics and computationalbiology (ieee CIBCB 2022) was held from August 15th-17th in Ottawa, Canada. This conference has been held annually since 2004. After two years of virtual conferences, ieee CIBCB 2022 was held primarily in person, with some remote participation. It was great to be back with friends and colleagues!
The proceedings contain 38 papers. The topics discussed include: a multiobjective evolutionary algorithm for colon cancer biomarkers identification on gene expression data;machine learning identifies novel microRNA bi...
ISBN:
(纸本)9798350356632
The proceedings contain 38 papers. The topics discussed include: a multiobjective evolutionary algorithm for colon cancer biomarkers identification on gene expression data;machine learning identifies novel microRNA biomarkers predictive for gastric cancer;methods for analyzing swallowing sound in dysphagia care: a telemedicine approach;a fast feature selection for interpretable modeling based on fuzzy inference systems;improving machine learning based sepsis diagnosis using heart rate variability;machine learning and gut microbiome for breast cancer screening;comprehensive modeling and question answering of cancer clinical practice guidelines using LLMs;and predicting metabolic reactions with a molecular transformer for drug design optimization.
The 2022 ieee Conference on computationalintelligence in bioinformatics and computationalbiology (ieee CIBCB 2022) was held from August 15th-17th in Ottawa, Canada. This conference has been held annually since 2004....
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The proceedings contain 38 papers. The topics discussed include: harnessing digital pathology and causal learning to improve eosinophilic esophagitis dietary treatment assignment;comparison of representations to evolv...
ISBN:
(纸本)9798350310177
The proceedings contain 38 papers. The topics discussed include: harnessing digital pathology and causal learning to improve eosinophilic esophagitis dietary treatment assignment;comparison of representations to evolve weighted contact networks with epidemic properties;ai deployment in medical devices- ethical and regulatory reflections, beyond data protection and bias - EU perspective;bacterial phenotype prediction based on methylation site profiles;effective vaccination strategy for infectious diseases by analyzing the age and comorbidity attributes of individuals on social network;a tissue-aware simulation framework for [18F]FLT spatiotemporal uptake in pancreatic ductal adenocarcinoma;towards EEG-based objective ADHD diagnosis support using convolutional neural networks;trustworthy artificial intelligence in medical applications: a mini survey;and pattern matching of positive and negative DNA sequences with general gaps and one-off constraints.
The proceedings contain 43 papers. The topics discussed include: non-invasive blood pressure measurement using a mobile phone camera;evaluation of frameworks for epidemic variants and infectivity using an evolutionary...
ISBN:
(纸本)9781665484626
The proceedings contain 43 papers. The topics discussed include: non-invasive blood pressure measurement using a mobile phone camera;evaluation of frameworks for epidemic variants and infectivity using an evolutionary algorithm;learning binary threshold networks for gene regulatory network modeling;multi-objective optimization for marker panel identification in single-cell data;automated portfolio generation for selection hyper-heuristics: an application to protein structure prediction on 2D HP model;identification of the prognostic signatures for isocitrate dehydrogenase mutant glioma;automated detection of ERP artifacts of auditory oddball paradigm by unsupervised machine learning algorithm;automatic diverse subset selection from enzyme families by solving the maximum diversity problem;exploring multi-objective deep reinforcement learning methods for drug design;and inference of genetic networks using random forests: a quantitative weighting method for gene expression data.
Automated multi-label chest X-rays (CXR) image classification has achieved substantial progress in clinical diagnosis via utilizing sophisticated deep learning approaches. However, most deep models have high computati...
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Automated multi-label chest X-rays (CXR) image classification has achieved substantial progress in clinical diagnosis via utilizing sophisticated deep learning approaches. However, most deep models have high computational demands, which makes them less feasible for compact devices with low computational requirements. To overcome this problem, we propose a knowledge distillation (KD) strategy to create the compact deep learning model for the real-time multi-label CXR image classification. We study different alternatives of CNNs and Transforms as the teacher to distill the knowledge to a smaller student. Then, we employed explainable artificial intelligence (XAI) to provide the visual explanation for the model decision improved by the KD. Our results on three benchmark CXR datasets show that our KD strategy provides the improved performance on the compact student model, thus being the feasible choice for many limited hardware platforms. For instance, when using DenseNet161 as the teacher network, EEEA-Net-C2 achieved an AUC of 83.7%, 87.1%, and 88.7% on the ChestX-ray14, CheXpert, and PadChest datasets, respectively, with fewer parameters of 4.7 million and computational cost of 0.3 billion FLOPS.
The proceedings contain 37 papers. The topics discussed include: protein secondary structure prediction based on physicochemical features and PSSM by SVM;the impact of SignalP 4.0 on the prediction of secreted protein...
ISBN:
(纸本)9781467358750
The proceedings contain 37 papers. The topics discussed include: protein secondary structure prediction based on physicochemical features and PSSM by SVM;the impact of SignalP 4.0 on the prediction of secreted proteins;predicting protein crystallization using a simple scoring card method;intellectual property protection for bioinformatics and computationalintelligence;NSC-GA: search for optimal shrinkage thresholds for nearest shrunken centroid;a study on the effect of different thermodynamic models for predicting pseudoknotted RNA secondary structures;an exploration into improving DNA motif inference by looking for highly conserved core regions;machine learning based search space optimization for drug discovery;RIPGA: RNA-RNA interaction prediction using genetic algorithm;and capturing hydrophobic moment using spectral coherence for protein secondary structure prediction.
The proceedings contain 37 papers. The topics discussed include: adversarial deep evolutionary learning for drug design;vaccinating a population is a changing programming problem;ring optimization of epidemic contact ...
ISBN:
(纸本)9781665401128
The proceedings contain 37 papers. The topics discussed include: adversarial deep evolutionary learning for drug design;vaccinating a population is a changing programming problem;ring optimization of epidemic contact networks;using clinical drug representations for improving mortality and length of stay predictions;genome-scale prediction of bacterial promoters;identification of genes associated with Alzheimer’s disease using evolutionary computation;automatic detection of necrotizing fasciitis: a dataset and early results;human activity recognition using convolutional neural networks;a comparison of novel representations for evolving epidemic networks;and dynamically regulated initialization for s-system modelling of genetic networks.
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