News

We are excited to share our new preprint, "A Frame-Level View and Image-Quality Annotation Tool for Fetal Echocardiography: Comparison with Spreadsheet Annotation," now available on arXiv. Congratulations to Azzam and all co-authors!

We are pleased to announce that Dr. Jieqiong Wang received the UNMC New Investigator Award in recognition of her research accomplishments and contributions to UNMC. Congratulations to Dr. Wang on this well deserved achievement!

We are excited to share our new study, “Predicting the Timing of Adolescent Drinking Onset from Baseline Clinical Data: A Stacked-Encoder Survival Framework with Embedding-Derived Biotypes.” Congratulations to Ruobing and the entire team on this new achievement!

Esther presents a poster on "Early AI Prediction of Survival in Metastatic Castration-Resistant Prostate Cancer Using Tumor Growth Rate" at the Great Plains Bioinformatics Conference 2026.

We are excited to share our new preprint, “Towards Whole-Study Screening for Congenital Heart Disease,” now available on arXiv. Congratulations to Azzam and all co-authors!

We are pleased to share that our study, “Classification of Adolescent Drinking via Behavioral, Biological, and Environmental Variables: A Machine Learning Approach with Bias Control,” is now published in Addiction Biology. Congratulations to Ruobing and all co-authors on this achievement!

We are excited to share that our manuscript, “Classification of Adolescent Drinking via Behavioral, Biological, and Environmental Variables: A Machine Learning Approach with Bias Control,” has been accepted for publication in Addiction Biology. Congratulations to Ruobing and all co-authors on this achievement!

We are pleased to share that a collaborative team led by Dr. Wan as Principal Investigator (PI) and Dr. Jieqiong Wang as Multiple Principal Investigator (MPI) has received a two-year R03 grant from the National Institutes of Health/National Cancer Institute (NIH/NCI).The project will focus on developing a multimodal artificial intelligence framework to characterize pediatric T-cell acute lymphoblastic leukemia (T-ALL) using data from the Gabriella Miller Kids First Pediatric Research Program. Congratulations to Dr. Wan lab and the Wang Lab on this exciting achievement and collaboration!

We are pleased to share that Dr. Jieqiong Wang has been selected as a recipient of the UNMC New Investigator Award, presented by the Office of the Vice Chancellor for Research (VCR). The award recognizes outstanding early-career investigators and their contributions to research at UNMC. The award ceremony will be held on October 29, 2026. Congratulations to Dr. Wang on this well-deserved recognition!

We are thrilled to announce that the Wang Lab has been awarded a new NIH R21 grant. The project will develop an automated BNST segmentation algorithm and explore the role of the BNST in adolescent alcohol use. Congratulations to the entire team on this exciting achievement!

Our paper "WIMOAD: Weighted Integration of Multi-Omics Data with Meta Learning for Alzheimer’s Disease Diagnosis" is accepted by Journal of Alzheimers Disease. Congratulations to all co-authors!

We are pleased to announce that the Wang Lab has been awarded a competitive CHRI AI Grant!. The project will leverage AI and ultrasound imaging to develop multi-scale fetal biological age clocks. Congratulations to the entire team on this exciting achievement!

We are pleased to announce that the Wang Lab has received funding through a four-year NSF Focused EPSCoR Collaboration grant involving UNMC, the University of Idaho, and Clemson University. The project will support the development of multi-omics foundation models and advanced cell segmentation methods. Congratulations to Dr. Wan, Dr. Wang, and all participating lab members!

Ruobing presents a poster on "Classifying Adolescent Drinking from Baseline Behavioral, Biological, and Environmental Features" at 2026 Big Ten Neuroscience Annual Meeting.

Ruobing presents a digital poster on "Scalable AI for Fetal Ultrasound: Congenital Heart Disease Detection and Foundations for Downstream Prenatal Imaging Tasks" at 2026 Big Ten Neuroscience Annual Meeting.

Ruobing presents a digital poster on "Semi-Supervised Domain Adversarial Automated Segmentation Pipeline for the Bed Nucleus of the Stria Terminalis" at 2026 Big Ten Neuroscience Annual Meeting.

Ruobing presents a poster on "Classifying Adolescent Drinking from Baseline Behavioral, Biological, and Environmental Features" at the AI in Health Conference 2026.

Esther presents a poster on "Early AI Prediction of Survival in Metastatic Castration-Resistant Prostate Cancer Using Tumor Growth Rate" at the AI in Health Conference 2026.

Ruobing presents a digital poster on "Semi-Supervised Domain Adversarial Automated Segmentation Pipeline for the Bed Nucleus of the Stria Terminalis" at the AI in Health Conference 2026.

Azzam presents a digital poster on "Scalable AI for Fetal Ultrasound: Congenital Heart Disease Detection and Foundations for Downstream Prenatal Imaging Tasks" at the AI in Health Conference 2026.

We are pleased to announce that our team has been awarded a new Nebraska Research Initiative (NRI) grant, with Nebraska Research Initiative support for an innovative research project focused on prenatal health. In this project, Dr. Wang will serve as Co-Project Leader. The grant will support our efforts to leverage artificial intelligence (AI) to predict the risk of congenital heart disease in prenatal fetuses. Congratulations to the entire team on this exciting achievement!

Congratulations to Ziyang Xu on accepting a PhD offer from the University of Illinois Urbana-Champaign (UIUC)! We are proud to celebrate this exciting milestone and wish you continued success in your doctoral studies.

Dr. Wang was invited to speak at the Nexus Informatics Conference, where she delivered a presentation titled "Advancing Prenatal Congenital Heart Disease Screening through Artificial Intelligence." at Children’s Mercy Research Institute.

Ruobing presents a poster on "Classifying Adolescent Drinking from Baseline Behavioural, Biological, and Environmental Features" at CoNDA Center Colloquium.

Esther presents a poster on "Scalable AI for Fetal Ultrasound: Congenital Heart Disease Detection and Foundations for Downstream Prenatal Imaging Tasks" at CoNDA Center Colloquium.

Ruobing presents a poster on "Semi-supervised Domain Adversarial Automated Segmentation Pipeline for the Bed Nucleus of the Stria Terminalis" at CoNDA Center Colloquium.

A preprint version of our paper on "Early treatment outcome prediction in metastatic castration-resistant prostate cancer utilizing 3-month tumor growth rate (g-rate) based machine learning model" has been published in medRxiv (2026).

A preprint version of our paper on "Classification of Adolescent Drinking via Behavioral, Biological, and Environmental Features: A Machine Learning Approach with Bias Control" has been published in medRxiv (2026).

Dr. Wang is awarded the NIH/NIGMS Women's Health Supplemental Funding to the UNMC Center for Heart and Vascular Research (CHVR)! We will focus on developing AI models for reducing maternal stress and improving pregnancy experiences. Thanks for the generous support from NIH!

Esther presents poster "Early Clinical Decision-Making in Metastatic Castration-Resistant Prostate Cancer: A G-Rate Based AI model of Overall Survival Within Three Months of Therapy​" at Genetics, Cell Biology & Anatomy (GCBA) Symposium.

Our paper "nnU-BNST: Deep Learning-Based Automated Segmentation of the Bed Nucleus of the Stria Terminalis" was accepted by the MICCAI workshop MLMI 2025. Congratulations to Ziyang, Azzam, and all co-authors!

Dr. Wang gave a talk on "Advancing AI for Individualized Diagnosis and Prognosis: From Prenatal Heart Defects to Prostate Cancer Survival" at the 2025 International Conference on Intelligent Biology and Medicine (ICIBM 2025) in Columbus, OH.

Dr. Wang is awarded an NSF Smart and Connected Health (SCH) grant by NSF to develop a novel multi-modal deep learning and statistical framework to maximize health outcomes for breast cancer. It will be a four-year grant with a start date of Aug-01-2025. Congratulations!

Dr. Wang is awarded the Buffett Cancer Center American Cancer Society (ACS) Seed Grant, congratulations!

An abstract paper of "Development of g-rate based random forest machine learning model to predict overall survival for patients with metastatic prostate cancer" was published in "Cancer Research" of AACR 2025. Congratulations to Azzam!

An abstract paper of "Enhancing prostate pelvic multimodality data generating with conditional generative models: A Pix2Pix-based approach for MRI-to-PET synthesis" was published in "Cancer Research" of AACR 2025. Congratulations to Ruobing!

Dr. Wang gave a presentation on "The Association between Brain Age and DNA Methylation Age at the Global and the Local Level" at the CoNDA Center Colloquium.

Our poster "The Triple Network Model of Cocaine-use Disorder: Default Mode Network, Central Executive Network, and Salience Network" won the "Best Poster Award" at the CoNDA Center Colloquium. Congratulations to Ziyang!

An abstract paper of "g -Rate–based machine learning model to predict overall survival (OS) in patients with metastatic prostate cancer (mPC) while on treatment" was published in "Journal of Clinical Oncology." Congratulations to Dr. Wang and Azzam!

An abstract paper of "Enhancing prostate pelvic multimodality data generating with conditional generative models: A Pix2Pix-based approach for MRI-to-PET synthesis" was accepted by AACR Annual Meeting 2025. Congratulations to Ruobing!

A preprint version of our paper of "Functional Connectivity Alterations in Cocaine Use Disorder: Insights from the Triple Network Model and the Addictions Neuroclinical Assessment Framework" is now available on BioRxiv.

Our review paper of "A review of artificial intelligence-based brain age estimation and its applications for related diseases" was published in "Briefings in Functional Genomics." Congratulations to Azzam and all co-authors!