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ORCIDBioData Mining, Volume 16
Volume 16, Number 1, January 2023
- Peter Appiahene, Justice Williams Asare
, Emmanuel Timmy Donkoh, Giovanni Dimauro, Rosalia Maglietta:
Detection of iron deficiency anemia by medical images: a comparative study of machine learning algorithms. - Abdulrahman Alasiri, Konrad J. Karczewski, Brian S. Cole, Bao-Li Loza, Jason H. Moore, Sander W. Van der Laan, Folkert W. Asselbergs, Brendan J. Keating, Jessica van Setten:
LoFTK: a framework for fully automated calculation of predicted Loss-of-Function variants and genes. - Yun Jiang, Jinkun Dong, Tongtong Cheng, Yuan Zhang, Xin Lin, Jing Liang:
iU-Net: a hybrid structured network with a novel feature fusion approach for medical image segmentation. - Petr Rysavý, Filip Zelezný:
Reference-free phylogeny from sequencing data. - Davide Chicco, Giuseppe Jurman:
Ten simple rules for providing bioinformatics support within a hospital. - Shuo-Ming Ou, Ming-Tsun Tsai, Kuo-Hua Lee, Wei-Cheng Tseng, Chih-Yu Yang, Tz-Heng Chen, Pin-Jie Bin, Tzeng-Ji Chen, Yao-Ping Lin, Wayne Huey-Herng Sheu, Yuan-Chia Chu, Der-Cherng Tarng:
Prediction of the risk of developing end-stage renal diseases in newly diagnosed type 2 diabetes mellitus using artificial intelligence algorithms. - Sebastian Spänig, Alexander Michel, Dominik Heider:
Unsupervised encoding selection through ensemble pruning for biomedical classification. - Davide Chicco, Tiziana Sanavia, Giuseppe Jurman:
Signature literature review reveals AHCY, DPYSL3, and NME1 as the most recurrent prognostic genes for neuroblastoma. - Davide Chicco, Giuseppe Jurman:
The Matthews correlation coefficient (MCC) should replace the ROC AUC as the standard metric for assessing binary classification. - Philip J. Freda, Attri Ghosh, Elizabeth Zhang, Tianhao Luo, Apurva S. Chitre, Oksana Polesskaya, Celine L. St. Pierre, Jianjun Gao, Connor D. Martin, Hao Chen, Angel G. Garcia-Martinez, Tengfei Wang, Wenyan Han, Keita Ishiwari, Paul Meyer, Alexander Lamparelli, Christopher P. King, Abraham A. Palmer, Ruowang Li, Jason H. Moore:
Automated quantitative trait locus analysis (AutoQTL). - Scott M. Williams, Jason H. Moore:
Genetics and precision health: the ecological fallacy and artificial intelligence solutions. - Mengying Wang, Cuixia Lee, Zhenhao Wei, Hong Ji, Yingyun Yang, Cheng Yang:
Clinical assistant decision-making model of tuberculosis based on electronic health records. - Diego Arnal, Celeste Moya, Luigi Filippelli, Jaume Segura-Garcia, Sergi Maicas:
Bacteria spatial tracking in Urban Park soils with MALDI-TOF Mass Spectrometry and Specific PCR. - Nico Schmid, Mihnea Ghinescu, Moritz Schanz, Micha Christ, Severin Schricker, Markus Ketteler, Mark Dominik Alscher, Ulrich Franke, Nora Goebel:
Algorithm-based detection of acute kidney injury according to full KDIGO criteria including urine output following cardiac surgery: a descriptive analysis. - Nelson E. Ordóñez-Guillén, José Luis González Compeán, Ivan López-Arévalo, Miguel Contreras-Murillo, Edwin Aldana-Bobadilla:
Machine learning based study for the classification of Type 2 diabetes mellitus subtypes. - Wei Li, Minghang Zhang, Siyu Cai, Liangliang Wu, Chao Li, Yuqi He, Guibin Yang, Jinghui Wang, Yuanming Pan:
Neural network-based prognostic predictive tool for gastric cardiac cancer: the worldwide retrospective study. - Elnaz Ziad, Somayeh Sadat, Farshad Farzadfar, Mohammad-Reza Malekpour:
Prescription pattern analysis of Type 2 Diabetes Mellitus: a cross-sectional study in Isfahan, Iran. - Sofia Martins, Roberta Coletti, Marta B. Lopes:
Disclosing transcriptomics network-based signatures of glioma heterogeneity using sparse methods. - Zarif L. Azher, Anish Suvarna, Ji-Qing Chen, Ze Zhang, Brock C. Christensen, Lucas A. Salas, Louis J. Vaickus, Joshua J. Levy:
Assessment of emerging pretraining strategies in interpretable multimodal deep learning for cancer prognostication. - Guohua Huang, Xiaohong Huang, Wei Luo:
6mA-StackingCV: an improved stacking ensemble model for predicting DNA N6-methyladenine site. - Jiyoon Park, Jae Won Lee, Mira Park:
Comparison of cancer subtype identification methods combined with feature selection methods in omics data analysis. - David N. Nicholson, Faisal Alquaddoomi, Vincent Rubinetti, Casey S. Greene:
Changing word meanings in biomedical literature reveal pandemics and new technologies. - Tzong-Hann Yang, Yu-Fu Chen, Yen-Fu Cheng, Jue-Ni Huang, Chuan-Song Wu, Yuan-Chia Chu:
Optimizing age-related hearing risk predictions: an advanced machine learning integration with HHIE-S. - Jesse G. Meyer, Ryan J. Urbanowicz, Patrick C. N. Martin, Karen O'Connor, Ruowang Li, Pei-Chen Peng, Tiffani J. Bright, Nicholas P. Tatonetti, Kyoung-Jae Won, Graciela Gonzalez-Hernandez, Jason H. Moore:
ChatGPT and large language models in academia: opportunities and challenges. - Naya Nagy, Matthew Stuart-Edwards, Marius Nagy, Liam Mitchell, Athanasios Zovoilis:
Quantum analysis of squiggle data. - Qian Yan, Wenjiang Zheng, Boqing Wang, Baoqian Ye, Huiyan Luo, Xinqian Yang, Ping Zhang, Xiongwen Wang:
Correction: A prognostic model based on seven immune-related genes predicts the overall survival of patients with hepatocellular carcinoma. - Zhenxiang He, Xiaoxia Li, Yuling Chen, Nianzu Lv, Yong Cai:
Attention-based dual-path feature fusion network for automatic skin lesion segmentation. - Massimiliano Datres, Elisa Paolazzi, Marco Chierici, Matteo Pozzi, Antonio Colangelo, Marcello Dorian Donzella, Giuseppe Jurman:
Endoscopy-based IBD identification by a quantized deep learning pipeline. - John T. Gregg, Jason H. Moore:
STAR_outliers: a python package that separates univariate outliers from non-normal distributions. - Weiquan Pan, Faning Long, Jian Pan:
ScInfoVAE: interpretable dimensional reduction of single cell transcription data with variational autoencoders and extended mutual information regularization. - Marian Petrica, Ionel Popescu:
Inverse problem for parameters identification in a modified SIRD epidemic model using ensemble neural networks. - Maryam Ramezani, Amirhossein Takian, Ahad Bakhtiari, Hamid R. Rabiee, Sadegh Ghazanfari, Saharnaz Sazgarnejad:
Research agenda for using artificial intelligence in health governance: interpretive scoping review and framework. - Sana Munquad, Asim Bikas Das:
DeepAutoGlioma: a deep learning autoencoder-based multi-omics data integration and classification tools for glioma subtyping. - Jing Luo, Jundong Li, Qi Mao, Zhenghao Shi, Haiqin Liu, Xiaoyong Ren, Xinhong Hei:
Overlapping filter bank convolutional neural network for multisubject multicategory motor imagery brain-computer interface. - Tanapol Kosolwattana, Chenang Liu, Renjie Hu, Shizhong Han, Hua Chen, Ying Lin:
A self-inspected adaptive SMOTE algorithm (SASMOTE) for highly imbalanced data classification in healthcare.
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last updated on 2024-09-19 23:33 CEST by the dblp team
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