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Advanced machine learning and health-related multi-omics data

Guest Editors:
Alejandro Rodriguez Gonzalez: Universidad Politécnica de Madrid, Spain
Wei Lan Guangxi University, China

BMC Medical Informatics and Decision Making, BMC Medical Genomics welcomed submissions to Collection on Advanced machine learning and health-related multi-omics data.

The development of novel techniques based on data-driven approaches, especially focused on artificial intelligence techniques, for the study of human health from a computational perspective, is gaining momentum nowadays. Different types of available data are making new types of analysis possible, opening new research areas. Multi-omics data are a particular case of data combining different sources of information that can be used for deeper analysis of human health, to have a better understanding of underlying connections and associations. The application of artificial intelligence can be of particular interest to unveil such complex relationships, with potential insights in real-world scenarios, including the clinical application.

Please email Patrik Flammer, the in-house editor for BMC Medical Genomics, ( or Piero Lo Monaco, the in-house editor for BMC Medical Informatics and Decision Making ( if you would like more information. 

Meet the Guest Editors

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Prof. Alejandro Rodríguez-González, Universidad Politécnica de Madrid, Spain

Prof. Alejandro Rodríguez-González, Ph.D., is a Full Professor and Principal Investigator of the Medical Data Analysis laboratory (MEDAL) at the Center for Biomedical Technology in Universidad Politécnica de Madrid. His main research expertise is focused on applying machine learning methods to different types of biomedical information with a special focus on the area of disease networks to increase our current understanding of diseases and their relationships.

Dr. Wei Lan, Guangxi University, China
Dr. Wei Lan received his PhD degree from Central South University in 2016. He is currently an associate professor of the School of Computer, electronic and information at Guangxi University. His research interests include bioinformatics and artificial intelligence. He has published more than 50 refereed papers in international journals and conferences. He has been serving as an associate editor of frontiers in genetics and editorial board member of BMC Medical Genomics, BMC Digital Health, BMC Medical Informatics and Decision Making, Frontiers in Bioscience-Landmark and BioMed Research International.


About the collection

This cross-journal collection welcomed articles presenting novel developments and applications of advanced machine learning methods in multi-omics data with clinical relevance for human health, from the perspective of either medical informatics or genomics, with particular attention to deep learning and reinforcement learning methods. For submissions reporting associations between a specific parameter and a health condition, the collection considered studies that include at least an experimental validation step to support their findings. Studies about specific applications, such as high-dimensional statistics & omics data analysis and diagnostic tools, or novel software or databases were also considered.

In this context, potential lines of interest, include, but are not limited to:

  • Multi-omic data integration methods for machine learning analysis
  • Explainable machine learning methods for multi-omic data
  • Design and development of deep-learning/reinforcement learning based methods for multi-omic data

Image credit: © naddi / iStock

  1. An ever-increasing amount of data on a person’s daily functioning is being collected, which holds information to revolutionize person-centered healthcare. However, the full potential of data on daily functioni...

    Authors: Esther R.C. Janssen, Ilona M. Punt, Johan van Soest, Yvonne F. Heerkens, Hillegonda A. Stallinga, Huib ten Napel, Lodewijk W. van Rhijn, Barend Mons, Andre Dekker, Paul C. Willems and Nico L.U. van Meeteren
    Citation: BMC Medical Informatics and Decision Making 2024 24:184
  2. Machine learning (ML) classifiers are increasingly used for predicting cardiovascular disease (CVD) and related risk factors using omics data, although these outcomes often exhibit categorical nature and class...

    Authors: Gabin Drouard, Juha Mykkänen, Jarkko Heiskanen, Joona Pohjonen, Saku Ruohonen, Katja Pahkala, Terho Lehtimäki, Xiaoling Wang, Miina Ollikainen, Samuli Ripatti, Matti Pirinen, Olli Raitakari and Jaakko Kaprio
    Citation: BMC Medical Informatics and Decision Making 2024 24:116
  3. This study aimed to construct a coronary heart disease (CHD) risk-prediction model in people living with human immunodeficiency virus (PLHIV) with the help of machine learning (ML) per electronic medical recor...

    Authors: Zengjing Liu, Zhihao Meng, Di Wei, Yuan Qin, Yu Lv, Luman Xie, Hong Qiu, Bo Xie, Lanxiang Li, Xihua Wei, Die Zhang, Boying Liang, Wen Li, Shanfang Qin, Tengyue Yan, Qiuxia Meng…
    Citation: BMC Medical Informatics and Decision Making 2024 24:110
  4. Acute pancreatitis (AP) is a common systemic inflammatory disease resulting from the activation of trypsinogen by various incentives in ICU. The annual incidence rate is approximately 30 out of 100,000. Some p...

    Authors: Zhonghua Lu, Yan Tang, Ruxue Qin, Ziyu Han, Hu Chen, Lijun Cao, Pinjie Zhang, Xiang Yang, Weili Yu, Na Cheng and Yun Sun
    Citation: BMC Medical Genomics 2024 17:93
  5. Class imbalance remains a large problem in high-throughput omics analyses, causing bias towards the over-represented class when training machine learning-based classifiers. Oversampling is a common method used...

    Authors: Samuel Cusworth, Georgios V. Gkoutos and Animesh Acharjee
    Citation: BMC Medical Informatics and Decision Making 2024 24:90
  6. MECP2 duplication syndrome (MDS) is a rare X-linked genomic disorder that primarily affects males. It is characterized by delayed or absent speech development, severe motor and cognitive impairment, and recurrent...

    Authors: Lan Zeng, Hui Zhu, Jin Wang, Qiyan Wang, Ying Pang, Zemin Luo, Ai Chen, Shengfang Qin and Shuyao Zhu
    Citation: BMC Medical Genomics 2024 17:54
  7. Chronic kidney disease-mineral and bone disorder (CKD-MBD) is characterized by bone abnormalities, vascular calcification, and some other complications. Although there are diagnostic criteria for CKD-MBD, in s...

    Authors: Yuting Li, Yukuan Lou, Man Liu, Siyi Chen, Peng Tan, Xiang Li, Huaixin Sun, Weixin Kong, Suhua Zhang and Xiang Shao
    Citation: BMC Medical Informatics and Decision Making 2024 24:36
  8. Synthetic data is an emerging approach for addressing legal and regulatory concerns in biomedical research that deals with personal and clinical data, whether as a single tool or through its combination with o...

    Authors: Imanol Isasa, Mikel Hernandez, Gorka Epelde, Francisco Londoño, Andoni Beristain, Xabat Larrea, Ane Alberdi, Panagiotis Bamidis and Evdokimos Konstantinidis
    Citation: BMC Medical Informatics and Decision Making 2024 24:27
  9. Sexually transmitted infections (STIs) are a significant global public health challenge due to their high incidence rate and potential for severe consequences when early intervention is neglected. Research sho...

    Authors: Mengjie Hu, Han Peng, Xuan Zhang, Lefeng Wang and Jingjing Ren
    Citation: BMC Medical Informatics and Decision Making 2024 24:24
  10. Lung cancer is a highly prevalent malignancy worldwide and is associated with high mortality rates. While the involvement of endoplasmic reticulum (ER) stress in the development of lung adenocarcinoma (LUAD) h...

    Authors: Ying Liu, Wei Lin, Hongyan Qian, Ying Yang, Xuan Zhou, Chen Wu, Xiaoxia Pan, Yuan Liu and Gaoren Wang
    Citation: BMC Medical Genomics 2024 17:12
  11. With the change of lifestyle, the occurrence of coronary artery disease presents a younger trend, increasing the medical and economic burden on the family and society. To reduce the burden caused by this disea...

    Authors: Jiayu Wang, Yikang Xu, Lei Liu, Wei Wu, Chunjian Shen, Henan Huang, Ziyi Zhen, Jixian Meng, Chunjing Li, Zhixin Qu, Qinglei he and Yu Tian
    Citation: BMC Medical Informatics and Decision Making 2023 23:297
  12. Invasive detection methods such as liver biopsy are currently the gold standard for diagnosing liver cirrhosis and can be used to determine the degree of liver fibrosis and cirrhosis. In contrast, non-invasive...

    Authors: Xiaopei Liu, Dan Liu, Cong’e Tan and Wenzhe Feng
    Citation: BMC Medical Informatics and Decision Making 2023 23:294
  13. In this paper, we present a framework for developing a Learning Health System (LHS) to provide means to a computerized clinical decision support system for allied healthcare and/or nursing professionals. LHSs ...

    Authors: Mark van Velzen, Helen I. de Graaf-Waar, Tanja Ubert, Robert F. van der Willigen, Lotte Muilwijk, Maarten A. Schmitt, Mark C. Scheper and Nico L. U. van Meeteren
    Citation: BMC Medical Informatics and Decision Making 2023 23:279
  14. The goal of this study was to assess the effectiveness of machine learning models and create an interpretable machine learning model that adequately explained 3-year all-cause mortality in patients with chroni...

    Authors: Chenggong Xu, Hongxia Li, Jianping Yang, Yunzhu Peng, Hongyan Cai, Jing Zhou, Wenyi Gu and Lixing Chen
    Citation: BMC Medical Informatics and Decision Making 2023 23:267
  15. Individuals diagnosed with Fanconi anemia (FA), an uncommon disorder characterized by chromosomal instability affecting the FA signaling pathway, exhibit heightened vulnerability to the onset of myelodysplasti...

    Authors: Lixian Chang, Li Zhang, Beibei Zhao, Xuelian Cheng, Yang Wan, Ranran Zhang, Weiping Yuan, Xingjie Gao and Xiaofan Zhu
    Citation: BMC Medical Genomics 2023 16:290
  16. Accurate identification of venous thromboembolism (VTE) is critical to develop replicable epidemiological studies and rigorous predictions models. Traditionally, VTE studies have relied on international classi...

    Authors: Jeffrey Wang, Joao Souza de Vale, Saransh Gupta, Pulakesh Upadhyaya, Felipe A. Lisboa, Seth A. Schobel, Eric A. Elster, Christopher J. Dente, Timothy G. Buchman and Rishikesan Kamaleswaran
    Citation: BMC Medical Informatics and Decision Making 2023 23:262
  17. Smartwatches have become increasingly popular in recent times because of their capacity to track different health indicators, including heart rate, patterns of sleep, and physical movements. This scoping revie...

    Authors: Mohsen Masoumian Hosseini, Seyedeh Toktam Masoumian Hosseini, Karim Qayumi, Shahriar Hosseinzadeh and Seyedeh Saba Sajadi Tabar
    Citation: BMC Medical Informatics and Decision Making 2023 23:248
  18. This research aimed to develop a model for individualized treatment decision-making in inoperable elderly patients with esophageal squamous cell carcinoma (ESCC) using machine learning methods and multi-modal ...

    Authors: Yong Huang, Xiaoyu Huang, Anling Wang, Qiwei Chen, Gong Chen, Jingya Ye, Yaru Wang, Zhihui Qin and Kai Xu
    Citation: BMC Medical Informatics and Decision Making 2023 23:237
  19. LMNA gene encodes lamin A/C protein which participates in the construction of nuclear lamina, the mutations of LMNA result in a wide variety of diseases known as laminopathies. LMNA-related dilated cardiomyopathy...

    Authors: Lei Chang, Rong Huang, Jianzhou Chen, Guannan Li, Guangfei Shi, Biao Xu and Lian Wang
    Citation: BMC Medical Genomics 2023 16:229
  20. This retrospective study aims to validate the effectiveness of artificial intelligence (AI) to detect and classify non-mass breast lesions (NMLs) on ultrasound (US) images.

    Authors: Guoqiu Li, Hongtian Tian, Huaiyu Wu, Zhibin Huang, Keen Yang, Jian Li, Yuwei Luo, Siyuan Shi, Chen Cui, Jinfeng Xu and Fajin Dong
    Citation: BMC Medical Informatics and Decision Making 2023 23:174
  21. Diabetic peripheral neuropathy (DPN) is a common complication of diabetes. Predicting the risk of developing DPN is important for clinical decision-making and designing clinical trials.

    Authors: Xiaoyang Lian, Juanzhi Qi, Mengqian Yuan, Xiaojie Li, Ming Wang, Gang Li, Tao Yang and Jingchen Zhong
    Citation: BMC Medical Informatics and Decision Making 2023 23:146
  22. As the first point of contact for patients with health issues, general practitioners (GPs) are frequently confronted with patients presenting with non-specific symptoms of unclear origin. This can result in de...

    Authors: Dania Schütze, Svea Holtz, Michaela C. Neff, Susanne M. Köhler, Jannik Schaaf, Lena S. Frischen, Brita Sedlmayr and Beate S. Müller
    Citation: BMC Medical Informatics and Decision Making 2023 23:144
  23. Atherosclerosis (AS) is a leading cause of morbidity and mortality in older patients and features progressive formation of plaques in vascular tissues. With the progression of atherosclerosis, plaque rupture m...

    Authors: Zhanli Peng, Kangjie Wang, Shenming Wang, Ridong Wu and Chen Yao
    Citation: BMC Medical Genomics 2023 16:139
  24. The aim of this study was to construct a model used for the accurate diagnosis of Atopic dermatitis (AD) using pyroptosis related biological markers (PRBMs) through the methods of machine learning.

    Authors: Wenfeng Wu, Gaofei Chen, Zexin Zhang, Meixing He, Hongyi Li and Fenggen Yan
    Citation: BMC Medical Genomics 2023 16:138
  25. Glycosylation involved in various biological function, aberrant glycosylation plays an important role in cancer development and progression. Glycosyltransferase 8 domain containing 1 (GLT8D1) and GLT8D2, as me...

    Authors: Huimei Xu, Ke Huang, Yimin Lin, Hang Gong, Xueni Ma and Dekui Zhang
    Citation: BMC Medical Genomics 2023 16:123

    The Correction to this article has been published in BMC Medical Genomics 2023 16:136