Dr. Chien-Jen Chen earned his Sc.D. in epidemiology and human genetics from Johns Hopkins University (1983). He was a professor at National Taiwan University (1983–2006) and a research fellow at Academia Sinica (1986–2005), later serving as a distinguished research fellow (2006–2015) and vice president (2011–2015). He directed NTU’s Graduate Institute of Public Health (1993–1994), founded the Graduate Institute of Epidemiology (1994–1997), and was the dean of the College of Public Health (1999–2002). In government, he served as Minister of Health (2003–2005), Minister of the National Science Council (2006–2008), Premier (2023–2024), and the 14th Vice President of Taiwan (2016–2020). He is currently an academician and distinguished professor at Genomics Research Center of Academia Sinica.

For over 40 years, Dr. Chen has advanced molecular and genomic epidemiology, particularly in chronic arsenic poisoning and virus-induced cancers. His research on arsenic contamination spurred global mitigation efforts, and his work on hepatitis B shaped the viral load paradigm in clinical management. He has authored over 815 scientific articles and 75+ books/chapters, with 134,000+ citations (H-index: 161 as of March 1, 2025). Ranked Taiwan’s top medical scientist in 2022 (Research.com), he is an academician of Academia Sinica (1998) and a member of the World Academy of Sciences (2005), Mongolian Academy of Sciences (2007, honorary), US National Academy of Sciences (2017), and Pontifical Academy of Sciences (2021).

Precision health refers to the tailoring of disease prevention, screening, diagnosis, and treatment to the unique characteristics of an individual. It does not literally mean the creation of drugs or medical devices customized to a patient, but rather the ability to classify individuals into subpopulations that differ in their susceptibility to a particular disease, in the biology or prognosis of those diseases they may develop, or in their response to a specific treatment. Preventive or therapeutic interventions can then be concentrated on those who will benefit, sparing expense and side effects for those who will not.

Natural history of disease refers to the progression of a disease process in an individual over time, in the absence of treatment. It includes four stages: susceptibility, subclinical disease, clinical disease, and recovery/disability/death. Disease progression is driven by multiple factors, and end-stage disease is only a tip of iceberg. There exists individual variability in the disease progression with various driving factors at different stages. Prediction of disease progression is essential for precision health, and long-term follow-up studies are required to elucidate risk predictors of disease progression. The prediction of the risk of disease progression and the benefit of healthcare management is essential for the daily practice of healthcare workers.

Predictive medicine entails predicting the probability of disease and instituting preventive measures in order to either prevent the disease or significantly decrease its impact upon the patient by limiting disability or preventing mortality. It is intended for both healthy individuals (disease prediction) and for those with diseases (treatment prediction) with the purpose to predict susceptibility to a particular disease and to predict progression and treatment response for a given disease.

The predictors include modifiable and unmodifiable biosignatures. Age, gender, race, and genotypes are unmodifiable predictors; while anthropometric characteristics, dietary intake, lifestyle habits, and infection markers are modifiable predictors. Along with the rapid development in biomedical technology (genomics, transcriptomics, proteomics, glycomics, lipidomics, metabolomics, microbiomics, and medical images), each individual will have a virtual cloud of billions of biosignatures in coming years. Through the analysis of this health data cloud using artificial intelligence, it becomes possible to predict health status and treatment response by monitoring self-parameters.

Risk calculators, are widely used in precision health and predictive medicine. They
integrate several predictors into one measure of absolute risk using a regression model, usually in the form of risk score. Uncertainty about clinical interpretation of a single abnormal laboratory parameter can be improved using this method,
allowing for appropriate recognition of clinically important risk in persons with several but seemingly marginal risk factors that may otherwise not raise clinical concerns.

Many risk calculators have been developed and validated for the prediction of major cancers and cardiometabolic diseases in Taiwan. In our REVEAL-HBV/HCV Study, we have derived risk calculators for the prediction of cirrhosis and hepatocellular carcinoma in patients affected with chronic hepatitis B or C. These prediction models including age, gender, family history of liver cancer, viral infection biomarkers, liver inflammation index, alcohol consumption. These risk calculators have very good performance assessed through the area under the receiver operating characteristic curve (AUROC), calibration plots, and Brier scores. They are useful for patient-physician communication, clinical decision on follow-up examination and antiviral therapy, and national health resource allocation.

In the EVB-NPC Study, we have developed the risk calculator for predicting nasopharyngeal carcinoma (NPC), a unique cancer for Chinese populations. The calculator incorporated biosignatures including Epstein-Barr virus (EBV) infection markers, family NPC history and cigarette smoking. New EBV biomarkers have been identified to improve the early diagnosis of NPC.

In the GELAC Study, we have identified 28 variants at 25 independent loci for the prediction of lung adenocarcinoma. A polygenic risk score was derived and had good performance for predicting lung adenocarcinoma in East Asians, especially in never smokers.

James C. Lin is Professor Emeritus at the University of Illinois Chicago, where he has served as Head of the Bioengineering Department, Director of the Robotics and Automation Laboratory, and Director of Special Projects in Engineering. He held professorships in electrical and computer engineering, bioengineering, physiology and biophysics, and physical and rehabilitation medicine. He received the BS, MS and PhD degrees in electrical engineering from the University of Washington, Seattle.

Professor Lin is a Fellow of AAAS, AIMBE and URSI, and a Life Fellow of IEEE. He is recognized as a ScholarGPS Highly Ranked Scholar-Lifetime and an Elsevier Top Worldwide Scientists in their fields for Career Impact. He held a NSC Research Chair (1993 to 1997) and served for many years as an IEEE-EMBS distinguished lecturer. He is a recipient of the d’Arsonval Medal from the Bioelectromagnetics Society, IEEE EMC Transactions Prize Paper Award, IEEE COMAR Recognition Award, and CAPAMA Outstanding Leadership and Service Awards. He served as a member of U.S. President’s Committee for National Medal of Science (1992 and 1993) and as Chairman of Chinese American Academic & Professional Convention (1993).

Dr. Lin has served in leadership positions of several scientific and professional organizations including President of the Bioelectromagnetics Society, Chairman of the International Scientific Radio Union (URSI) Commission on Electromagnetics in Biology and Medicine, Co-Chair of URSI Inter-Commission Working Group on Solar Power Satellite, Chairman of the IEEE Committee on Man and Radiation, Vice President US National Council on Radiation Protection and Measurements (NCRP), and member of International Commission on Nonionizing Radiation Protection (ICNIRP). He also served on numerous advisory committees and panels for the U.S. Congress, Office of the U.S. President, National Academy of Sciences, National Research Council, National Science Foundation, National Institutes of Health, Marconi Foundation, and the World Health Organization.

Professor Lin has edited 11 and authored 4 books including Noninvasive Physiological Measurement: Wireless Microwave Sensing (CRC Press, 2024) and Auditory Effects of Microwave Radiation (Springer, 2021), authored 450 journal papers, magazine articles and book chapters, and made over 300 conference presentations. He has made many fundamental scientific contributions to electromagnetics in biology and medicine including microwave auditory effects and microwave thermoacoustic tomography. He has pioneered several medical applications of RF and microwave energies including invention of minimally invasive microwave ablation treatment for cardiac arrhythmia, and noncontact and noninvasive microwave sensing of physiological signatures and vital signs. He has chaired several international conferences including IEEE, BEMS and ICST (founding chairman of Wireless Mobile Communication and Healthcare - MobiHealth Conference). He was Editor-in-Chief of the Bioelectromagnetics journal from 2006 to 2022, served as magazine columnist, book series editor, guest editor and member of the editorial boards of several journals. A member of Sigma Xi, Phi Tau Phi, Tau Beta Pi, and Golden Key honorary societies, and listed in American Men and Women of Science, Who’s Who in America, Who’s Who in Engineering, Who’s Who in the World, and Men of Achievement, among others.

Microwave ultrasound tomography (MUT) imaging systems use microwave-pulse-induced acoustic pressure waves to form planar or tomographic images. Since the generation and detection of microwave-pulse-induced acoustic pressure waves depend on dielectric permittivity and acoustic properties of tissue, MUT imaging possesses the characteristic features of a dual-modality imaging system. The unique attributes of high contrast offered by microwave absorption and fine spatial resolution furnished by ultrasound are being explored to provide a noninvasive and nonionizing imaging modality for classification of biological tissues. This paper begins with a review of the research being conducted in developing MUT imaging for biomedical applications. It discusses the science of microwave ultrasonic wave generation and propagation in biological tissues, the design of prototype MUT systems, and recent results from phantom models and experimental subjects.

Examples include circular and linear array configurations and application scenarios involving isolated tissues and organs as well as animal models of intraventricular hemorrhages in brain injury.

Koichi Ito received the Ph.D degree from Tokyo Institute of Technology, Japan.  He is currently a Professor Emeritus and Visiting Professor at the Center for Frontier Medical Engineering (CFME), Chiba University, Japan.  He served as Deputy Vice-President for Research and Director of the CFME, Chiba University.  His main research interests include antennas for medical applications, small antennas for mobile communications, research on evaluation of the interaction between electromagnetic fields and a human body by use of phantoms, and antenna systems for body-centric wireless communications.  Dr. Ito is a Life Fellow of IEEE, a Fellow of URSI, and a Fellow of IEICE, Japan.  He is the recipient of the 2020 Balthasar van der Pol Gold Medal from URSI.  He served as an Associate Editor for the IEEE Transactions on Antennas and Propagation, an AdCom member for the IEEE AP-S, a Distinguished Lecturer for the IEEE AP-S, a BoD member for the Bioelectromagnetics Society, General Chair of ISAP2012, an elected Delegate to the European Association on Antennas and Propagation, a Vice-President of the Japanese Society for Thermal Medicine, Chair of URSI Commission K, and IEEE AP-S President for 2019.  He currently serves as the inaugural Chair of the IEEE AP-S Technical Directions Committee.

Various therapeutic modalities, such as surgery, radiotherapy, chemotherapy, gene therapy, immunotherapy, electrochemotherapy, hyperthermia and ablation, have been utilized for cancer treatment. RF and microwave antenna technologies have greatly contributed to the advancement of cancer treatment. Hyperthermia and ablation, sometimes referred to as thermal therapies, use the thermal effect of electromagnetic fields generated by heating antennas.

Hyperthermia basically exploits the difference of thermal sensitivity between tumors and normal tissues. The target tumor is usually heated up to the range 42-45 °C resulting in less damage to the surrounding normal tissues. For external heating, sophisticated phased array antennas have been developed and employed. For internal heating, an array of well-designed thin antennas is directly inserted into the tumor.

RF or microwave ablation has been applied mainly for treatment of small-sized tumors. A thin electrode or an antenna is directly inserted into the tumor to heat well over 60 °C and its treatment time is usually around a few minutes, much shorter than hyperthermia treatment.

Image-guided thermal therapies have recently been developed and employed to further improve QOL (quality of life) of patients and to ease an operation for medical doctors. A magnetic resonance (MR) guided system has been introduced as a promising tool, although the cost is still rather high. A typical example is an MR-guided annular phased array which can produce therapeutic temperatures at any depth in the human body and visualize real-time 3D temperature mapping.

It seems impossible to use real human bodies for experimental evaluation of the performances of internal antennas in particular. Instead, computer simulation is usually performed with digital human-body models. However, experiments with physical human-body phantoms are indispensable to validate the results of numerical simulations or to minimize animal experiments.

A couple of further compelling challenges will be addressed at the end of the presentation including “theranostics” for cancer treatment that means a combination of therapeutics and diagnostics.

Dominique Schreurs (Fellow, IEEE) received the M.Sc. and Ph.D. degrees in electronic engineering from KU Leuven, Leuven, Belgium. As a Postdoctoral Fellow, she was a Visiting Scientist with Agilent Technologies, ETH Zürich, and the National Institute of Standards and Technology. She is currently a Full Professor with KU Leuven. Her research interests include microwave/mmWave metrology, device and circuit modeling, and subsystem design for wireless and biomedical applications. Since 2009, she has been on IEEE MTT-S AdCom in multiple roles. She was a Distinguished Microwave Lecturer (2012-2014) and the Editor-in-Chief of the IEEE Transactions on microwave theory and techniques (2014-2016). From 2018 to 2019, she was the President of the Microwave Theory and Technology Society (MTT-S). She was also the Co-Chair of the Technical Program Committee (TPC) for the International Microwave Symposium 2023 and the General Chair of IMBioC 2023. She was involved in multiple ARFTG conferences as Conference Chair or TPC Chair. She is also a past President of the ARFTG organization.

In research, it is a must to validate ideas by realistic proofs-of-concept (PoCs). The difficulty of conceiving experiment design is finding the optimal balance between time efficiency, cost, and effectiveness. Microwave engineering is characterized by a high dimensionality in experimental degrees of freedom, such as selecting among a wide choice in measurement instrumentation. The level of difficulty increases even more when the subjects are to advance the health of the community at large. This talk discusses the challenges that microwave engineers face when developing experimental set-ups targeting tests for microwave biomedical applications. The talk covers multiple emerging areas within this domain, ranging from in-vivo dielectric spectroscopy, characterizing liquids in vials, high-precision sensing of small concentrations, to vital sign dynamic sensing and ensuring exposure safety.