SUBJECTS : Data Mining | Machine Learning Algorithms | Large Scale Data Analysi
LATEST MANUSCRIPTS IN BioData Mining
- 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. BioData mining. 2023, 16 (1): 1
Cited : 1Read More - Sebastian Spänig, Alexander Michel, Dominik Heider. Unsupervised encoding selection through ensemble pruning for biomedical classification. BioData mining. 2023, 16 (1): 10Cited : 0Read More
- Mengying Wang, Cuixia Lee, Zhenhao Wei, Hong Ji, Yingyun Yang, Cheng Yang. Clinical assistant decision-making model of tuberculosis based on electronic health records. BioData mining. 2023, 16 (1): 11Cited : 0Read More
- 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. BioData mining. 2023, 16 (1): 12Cited : 2Read More
- Petr Ryšavý, Filip Železný. Reference-free phylogeny from sequencing data. BioData mining. 2023, 16 (1): 13Cited : 0Read More
- 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). BioData mining. 2023, 16 (1): 14Cited : 4Read More
- 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. BioData mining. 2023, 16 (1): 15Cited : 10Read More
- David N Nicholson, Faisal Alquaddoomi, Vincent Rubinetti, Casey S Greene. Changing word meanings in biomedical literature reveal pandemics and new technologies. BioData mining. 2023, 16 (1): 16Cited : 0Read More
- Weiquan Pan, Faning Long, Jian Pan. ScInfoVAE: interpretable dimensional reduction of single cell transcription data with variational autoencoders and extended mutual information regularization. BioData mining. 2023, 16 (1): 17Cited : 0Read More
- JiYoon Park, Jae Won Lee, Mira Park. Comparison of cancer subtype identification methods combined with feature selection methods in omics data analysis. BioData mining. 2023, 16 (1): 18Cited : 0Read More
- 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. BioData mining. 2023, 16 (1): 19Cited : 0Read More
- 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. BioData mining. 2023, 16 (1): 2Cited : 18Read More
- Jesse G Meyer, Ryan J Urbanowicz, Patrick C N Martin, Karen O'Connor, Ruowang Li, Pei-Chen Peng, Tiffani J Bright, Nicholas Tatonetti, Kyoung Jae Won, Graciela Gonzalez-Hernandez, Jason H Moore. ChatGPT and large language models in academia: opportunities and challenges. BioData mining. 2023, 16 (1): 20Cited : 65Read More
- 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. BioData mining. 2023, 16 (1): 21Cited : 2Read More
- Marian Petrica, Ionel Popescu. Inverse problem for parameters identification in a modified SIRD epidemic model using ensemble neural networks. BioData mining. 2023, 16 (1): 22Cited : 0Read More
