Development and Validation of a Photoplethysmography System for Noninvasive Monitoring of Hemoglobin Concentration by Hongyun Liu, Fulai Peng, Minlu Hu, Jinlong Shi, Guojing Wang, Haiming Ai, Weidong Wang

“…To facilitate real-time total hemoglobin (tHb) monitoring, a portable prototype of a noninvasive Hb detection system was developed, and the accuracy of Hb predicted based on partial least squares (PLS) as well as backpropagation artificial neural network (BP-ANN) models was validated. Results. …”
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Klasifikasi Pola Pergerakan Bola Mata Menggunakan Metode Multilayer Backpropagation by Karina Amadea, Fitra A. Bachtiar, Gusti Pangestu

“…The presence of a neural network in the iris, helps humans to be able to find out the response to all changes in the body including changes in the spirit of life, character or even a person's nature. …”
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Drug-induced autoimmune-like hepatitis: A disproportionality analysis based on the FAERS database. by Wangyu Ye, Yuan Ding, Meng Li, Zhihua Tian, Shaoli Wang, Zhen Liu

“…Positive signal drugs were identified using Proportional Reporting Ratio (PRR), Reporting Odds Ratio (ROR), Bayesian Confidence Propagation Neural Network (BCPNN), and Empirical Bayesian Geometric Mean (EBGM). …”
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DeepGenMon: A Novel Framework for Monkeypox Classification Integrating Lightweight Attention-Based Deep Learning and a Genetic Algorithm by Abdulqader M. Almars

“…This suggested framework leverages an attention-based convolutional neural network (CNN) and a genetic algorithm (GA) to enhance detection accuracy while optimizing the hyperparameters of the proposed model. …”
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Kombinasi Feature Selection Fisher Score dan Principal Component Analysis (PCA) untuk Klasifikasi Cervix Dysplasia by Krisan Aprian Widagdo, Kusworo Adi, Rahmat Gernowo

“…And then PCA transforms candidate features into a new uncorrelated dataset. Artificial Neural Network Backpropagation used to evaluate performance combination FScore PCA. …”
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Using Sequence Mining to Predict Complex Systems: A Case Study in Influenza Epidemics by Theyazn H. H. Aldhyani, Manish R. Joshi, Shahab A. AlMaaytah, Ahmed Abdullah Alqarni, Nizar Alsharif

“…This paper presents three adapting intelligence models: support vector machine regression (SVMR), artificial neural network using particle swarm optimisation (ANNPSO), and our intelligent time series (INTS) to predict influenza epidemics. …”
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Multisource Accident Datasets-Driven Deep Learning-Based Traffic Accident Portrait for Accident Reasoning by Chun-Hao Wang, Yue-Tian-Si Ji, Li Ruan, Joshua Luhwago, Yin-Xuan Saw, Sokhey Kim, Tao Ruan, Li-Min Xiao, Rui-Jue Zhou

“…Our multisource accident datasets-driven deep learning model is composed of the following three submodels: (1) the structured data accident model using our accident feature-driven bidirectional long short-term memory (Bi-LSTM) and accident feature-driven bidirectional conditional random field (Bi-CRF) model to extract labels, (2) the unstructured traffic accident data model using our accident feature-driven piecewise convolutional neural network (PCNN) model to identify the extracted labels, and (3) the semistructured traffic accident data processing model. …”
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Marigold: a machine learning-based web app for zebrafish pose tracking by Gregory Teicher, R. Madison Riffe, Wayne Barnaby, Gabrielle Martin, Benjamin E. Clayton, Josef G. Trapani, Gerald B. Downes

“…By leveraging a highly efficient, custom-designed neural network architecture, Marigold achieves reasonable training and inference speeds even on modestly powered computers lacking a discrete graphics processing unit. …”
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Risk factors and machine learning prediction models for intrahepatic cholestasis of pregnancy by Yingchun Ren, Xiaoying Shan, Gengchao Ding, Ling Ai, Weiying Zhu, Ying Ding, Fuzhou Yu, Yun Chen, Beijiao Wu

“…Thirteen machine learning techniques, including Random Forest, Support Vector Machine, and Artificial Neural Network, were employed. Based on their various classification performances on the training set, the top five models were selected for internal validation. …”
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Automatic Recognition of Authors Identity in Persian based on Systemic Functional Grammar by Fatemeh Soltanzadeh, Azadeh Mirzaei, Mohammad Bahrani, Shahram Modarres Khiabani

“…Multilayer perceptron classifier, a type of neural network, was used for learning phase which resulted in a desirable accuracy in evaluation phase. …”
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Evaluation of linear, nonlinear and ensemble machine learning models for landslide susceptibility assessment in southwest China by Bingwei Wang, Qigen Lin, Tong Jiang, Huaxiang Yin, Jian Zhou, Jinhao Sun, Dongfang Wang, Ran Dai

“…Linear models represented by logistic regression (LR), nonlinear models represented by support vector machine (SVM), artificial neural network (ANN) and classification 5.0 decision tree (C5.0 DT), and ensemble models represented by random forest (RF) and categorical boosting (Catboost) were selected. …”
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A multidimensional assessment of adverse events associated with paliperidone palmitate: a real-world pharmacovigilance study using the FAERS and JADER databases by Siyu Lou, Zhiwei Cui, Yingyong Ou, Junyou Chen, Linmei Zhou, Ruizhen Zhao, Chengyu Zhu, Li Wang, Zhu Wu, Fan Zou

“…Utilizing disproportionality analyses such as the reporting odds ratios (ROR), proportional reporting ratios (PRR), Bayesian confidence propagation neural network (BCPNN), and multi-item Poisson shrinkage (MGPS), significant associations between ADEs and paliperidone palmitate were evaluated. …”
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Quantifying the tumour vasculature environment from CD-31 immunohistochemistry images of breast cancer using deep learning based semantic segmentation by Tristan Whitmarsh, Wei Cope, Julia Carmona-Bozo, Roido Manavaki, Stephen-John Sammut, Ramona Woitek, Elena Provenzano, Emma L. Brown, Sarah E. Bohndiek, Ferdia A. Gallagher, Carlos Caldas, Fiona J. Gilbert, Florian Markowetz

“…We first used a U-Net based convolutional neural network, trained and validated using 36 partially annotated whole slide images from 27 patients, to segment vessel structures and tumour regions from which the measurements are taken. …”
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Loss of MEF2C function by enhancer mutation leads to neuronal mitochondria dysfunction and motor deficits in mice by Ali Yousefian-Jazi, Suhyun Kim, Jiyeon Chu, Seung-Hye Choi, Phuong Thi Thanh Nguyen, Uiyeol Park, Min-gyeong Kim, Hongik Hwang, Kyungeun Lee, Yeyun Kim, Seung Jae Hyeon, Hyewhon Rhim, Hannah L. Ryu, Grewo Lim, Thor D. Stein, Kayeong Lim, Hoon Ryu, Junghee Lee

“…Methods Convolutional neural network was used to identify an ALS-associated SNP located in the intronic region of MEF2C (rs304152), residing in a putative enhancer element. …”
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Safety profiles of IDH inhibitors: a pharmacovigilance analysis of the FDA Adverse Event Reporting System (FAERS) database by Ximu Sun, Han Zhou, Yanming Li, Yanhui Luo, Qixiang Guo, Yixin Sun, Chenguang Jia, Bin Wang, Maoquan Qin, Peng Guo

“…Disproportionality analyses including the reporting odds ratio and the Bayesian confidence propagation neural network were performed in data mining to assess IDH inhibitor-relatedAEs. …”
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Embryonic heat conditioning induces paternal heredity of immunological cross- tolerance: coordinative role of CpG DNA methylation and miR-200a regulation by Padma Malini Ravi, Tatiana Kisliouk, Shelly Druyan, Amit Haron, Mark A. Cline, Elizabeth R. Gilbert, Noam Meiri

“…Additionally, analysis of sperm methylation patterns in EHC mature chicks led to identification of genes associated with neuronal development and immune response, indicating potential neural network reorganization. Finally, miR-200a emerges as a regulator potentially involved in mediating the cross-tolerance effect.…”
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Response surface methodology and adaptive neuro-fuzzy inference system for adsorption of reactive orange 16 by hydrochar by J. Oliver Paul Nayagam, K. Prasanna

“…This study validated adaptive neuro-fuzzy inference system, an artificial neural network with a fuzzy inference system, using response surface methodology projected experimental run with Box–Behnken method.FINDINGS: The adaptive neuro-fuzzy inference system model is created alongside the response surface methodology model to compare experimental outcomes. …”
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Effects of feature selection and normalization on network intrusion detection by Mubarak Albarka Umar, Zhanfang Chen, Khaled Shuaib, Yan Liu

“…Random forest (RF) models performed better on NSL-KDD and UNSW-NB15 datasets with accuracies of 99.86% and 96.01%, respectively, whereas artificial neural network (ANN) achieved the best accuracy of 95.43% on the CSE–CIC–IDS2018 dataset. …”
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Prediksi Detak Jantung Berbasis LSTM pada Raspberry Pi untuk Pemantauan Kesehatan Portabel by Ahmad Foresta Azhar Zen, Eko Sakti Pramukantoro, Kasyful Amron, Viera Wardhani, Putri Annisa Kamila

“…LSTM models are a type of artificial neural network architecture known for their ability to handle sequential data effectively, making them highly suitable for sequential heart rate monitoring and prediction. …”
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A Local Adversarial Attack with a Maximum Aggregated Region Sparseness Strategy for 3D Objects by Ling Zhao, Xun Lv, Lili Zhu, Binyan Luo, Hang Cao, Jiahao Cui, Haifeng Li, Jian Peng

“…The increasing reliance on deep neural network-based object detection models in various applications has raised significant security concerns due to their vulnerability to adversarial attacks. …”
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