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Yale School of Medicine (YSM) has begun a new concentration within the computational biology and bioinformatics program, giving students the opportunity to earn a masters degree and the necessary training to become biomedical data scientists/biomedical informaticians.

It also aims to train students to meet the growing demand of professionals who can organize and analyze biomedical and healthcare data using the latest developments in AI and related areas, said Lucila Ohno-Machado, MD, PhD, deputy dean and chair for biomedical informatics.

Cynthia Brandt, MD, MPH, vice-chair for education and professor in the new section of biomedical informatics & data science says this is the first time the graduate program offers the degree with a focus on biomedical informatics. It is now accepting applications until December 1. The first group of students will start in September 2024.

More than a specialized degree, this program offers students the opportunity to understand and translate computational data to the bench and bedside, says Brandt.

Without the workforce and the individuals who understand how data is created, how it's captured, how it's stored, and how different computational methods are necessary to analyze it, it causes a limitation that slows down what you can learn from the data that scientists are creating, explains Brandt. Then it makes it more difficult to translate that data, which could be used for clinical trials and for medical advances.

The terminal masters degree in computational biology and bioinformatics (CBB) with a biomedical informatics concentration consists of 9 courses, three of which are core studies, says Brandt.

Foundational classes for this masters degree are Introduction to Health Informatics, Core Topics in Biomedical Informatics and Data Science or Modeling Biological Systems II, and Biomedical Data Science: Mining and Modeling.

Without the workforce and the individuals who understand how data is created, how it's captured, how it's stored, and how different computational methods are necessary to analyze it, it causes a limitation that slows down what you can learn from the data that scientists are creating.

The remaining courses are electives and can vary, depending on each students interests and research focus. With the help of an advisor, students will choose elective courses in biomedical informatics. Examples of courses in this area include Natural Language Processing, Clinical Decision Support and Clinical Database Management Systems & Ontologies.

Students entering the program who do not have a background in biology will be required to take a course in biology or genetics.

Brandt added that additional courses students take could also be offered in the Department of Statistics and Data Science (S&DS), Computer Science (CPSC), or Engineering. Once a Department of Biomedical Informatics and Data Science (BIDS) is established at YSM, as is planned, newly developed courses will also have that designation.

To complete the graduate program successfully, students will need to pass at least two courses with honor grades and complete coursework with an average of a High Pass. Additionally, Grant detailed, students will complete a masters degree project, where they will come up with an idea, write a research paper, and defend it. They will also present their project in a seminar where they will answer questions about it as well as breadth knowledge of their coursework and track of study at the end of the two-year program.

Students interested in pursuing a doctoral degree in computational biology and bioinformatics or biomedical informatics can do so at Yale, said Brandt. According to Brandt, most of the students who apply to a bioinformatics program already have a background in biology and math, computer science, statistics, or data science. However, such programs also accept students who have a predominant clinical or biology background if they have a facility for math, statistics, or computer science.

My goal would be to have 10 to 20 students in the first year [of the masters program] where 10% or 20% of them would decide that they want to go on and get a PhD, says Brandt.

Brandt says that it is crucial to train individuals who are able to ask research questions, know how to analyze research data and other kinds of data, and understand computation and other computational methods.

The CBB PhD has existed in Yales Biological and Biomedical Sciences (BBS) since 2003. However, the biomedical informatics concentration was recently incorporated as a new independent section at YSM with several new faculty members, according to Brandt.

The masters degree in computational biology and bioinformatics was originally created by Perry Miller, MD, PhD and Mark Gerstein, PhD, in 2004 with the program intended to be a step for those interested in pursuing a doctoral degree in computational biology and bioinformatics.

The creation of a new academic unit in biomedical informatics and data science in 2023 expanded the teaching faculty significantly, said Ohno-Machado.

In addition to Brandt, senior faculty in biomedical informatics and data science include Ohno-Machado; Hua Xu, PhD, professor and vice chair for research; Daniella Meeker, PhD; associate professor in biomedical informatics & data science and chief research information officer.

Newly recruited junior faculty in biomedical informatics and data science include Qingyu Chen, PhD; Hoon Cho, PhD, Mary-Anne Hartley, MD, PhD, MPH, Xenophon Papademetris, PhD; Kei-Hoi Cheung, PhD; Huan He, PhD, Na Hong, PhD, Mark Iscoe, MD, MHS; Richard Taylor, MD, MHS; Fongci Lin, PhD, Anthony Lisi, DC; and Kalpana Raja, PhD, who join the existing team of biomedical informatics research scientists.

The growing team of 31 faculty who have secondary appointments at biomedical informatics and data science currently includes representatives from the Yale Child Study Center and YSM departments of Dermatology, Emergency Medicine, Laboratory Medicine, Molecular Biophysics, Biochemistry, Neurology, Ophthalmology, Pathology, Pediatrics, Psychiatry, Surgery, and Therapeutic Radiology, in addition to faculty at YSPH, SEAS, FAS, and YSN.

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Future Data Scientists and Biomedical Informatics Researchers Will ... - Yale School of Medicine

Future of Data Science: Digicrome Academy

Data science has come a long way, evolving from a buzzword to a crucial discipline that influences every aspect of our lives. From healthcare to business, data science is transforming the way we make decisions and understand the world around us. But what does the future hold for this dynamic field? In this article, we will explore the exciting emerging trends and technologies that are shaping the future of data science.

Artificial Intelligence and Machine Learning

Artificial Intelligence (AI) and Machine Learning (ML) are at the forefront of the data science revolution. These technologies are becoming more powerful and accessible, allowing data scientists to build smarter and more efficient models. In the future, we can expect AI and ML to play an even more significant role in data-driven decision-making.

AI and ML will continue to enhance automation, enabling systems to make real-time predictions and recommendations. Whether its personalized marketing, healthcare diagnostics, or autonomous vehicles, AI and ML are poised to revolutionize various industries.

Big Data and Cloud Computing

As our world becomes increasingly digital, the volume of data generated is growing exponentially. Big Data technologies and cloud computing platforms are essential for managing and processing this vast amount of information. The future of data science will see even more sophisticated tools and techniques for handling Big Data.

Cloud-based data storage and processing solutions will become more accessible, allowing organizations of all sizes to harness the power of Big Data. This will enable quicker decision-making and more in-depth insights, driving innovation in numerous fields.

Explainable AI

While AI and ML offer incredible capabilities, their decision-making processes can sometimes seem like a black box, making it challenging to understand why a particular decision was made. In the future, explainable AI (XAI) will gain prominence. XAI aims to provide transparency and clarity in AI models, making it easier for humans to trust and interpret their decisions.

XAI will be crucial in applications where accountability and ethics are paramount, such as healthcare and finance. As AI continues to integrate into our lives, understanding its decisions will be essential.

Edge Computing

Edge computing involves processing data closer to where it is generated, rather than sending it to a centralized data center. This approach reduces latency and is especially important for applications that require real-time processing, like autonomous vehicles and IoT devices.

The future of data science will see increased focus on edge computing, enabling more efficient and responsive systems. This trend will also address privacy concerns by keeping sensitive data closer to its source.

Natural Language Processing (NLP)

NLP is a subfield of AI that focuses on enabling computers to understand and interact with human language. We already see NLP in action with virtual assistants like Siri and chatbots. However, the future will bring even more sophisticated NLP applications.

Advanced NLP models will improve language translation, sentiment analysis, and content recommendation. This will enhance communication and information access on a global scale.

Quantum Computing

Quantum computing is still in its infancy, but it holds the promise of solving complex problems exponentially faster than classical computers. In the future, quantum computers will revolutionize data science by handling massive datasets and optimization tasks that are currently beyond our capabilities.

Although quantum computing is not yet widely accessible, its an area to watch as it could transform data science and many other fields.

Responsible AI and Data Ethics

As data science continues to advance, questions of ethics and responsibility become increasingly important. The future will see more robust frameworks for ensuring that AI and data science are used in ways that are fair, unbiased, and respect privacy.

Regulations and guidelines will evolve to keep pace with technological developments. Responsible AI practices will be integral to building trust with users and stakeholders.

Conclusion

The future of data science is bright and full of possibilities. Emerging technologies like AI, Big Data, XAI, edge computing, NLP, and quantum computing are poised to reshape the way we collect, analyze, and interpret data. However, with great power comes great responsibility. Ensuring that these technologies are used ethically and responsibly will be a critical challenge in the years to come.

As data science continues to evolve, its impact on society will grow exponentially. From healthcare breakthroughs to more personalized shopping experiences, the future of data science promises to make our lives more efficient, convenient, and insightful. The only limit to its potential is our imagination and our commitment to using it for the greater good. So, lets embrace these emerging trends and technologies in data science and look forward to a brighter, data-driven future.

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The Future of Data Science: Emerging Trends and Technologies - Medium

UH Mnoa National Science Foundation Research Traineeship team

A new University of Hawaii at Mnoa graduate education program that is designed to train the next generation of data scientists in a multitude of skill sets to benefit the state, nation and the world earned a five-year, $3 million boost from the National Science Foundation (NSF).

The NSF Research Traineeship award will allow a cross-disciplinary group of researchers to develop an innovative graduate program that brings together engineering, computer science, social science, business and medicine to harness the power of data science. According to the U.S. Bureau of Labor Statistics, the employment of data scientists is projected to grow 35% from 2022 to 2032, much faster than the average for all occupations.

Currently in a time of extraordinary technological progress, particularly in data science and artificial intelligence, economic and other challenges, including the COVID-19 pandemic, have delayed the benefits of this progress for a majority of the population. In our state, progress in data science has the potential to address critical needs in power, transportation, healthcare and communications. To benefit Hawaiis residents, however, technological progress must consider economic, business and social factors.

The new cross-disciplinary program plans to train a new generation of 61 graduate students, including 41 funded trainees. The program incorporates novel mechanisms such as tailored course modules to better prepare the trainees with the unique skills needed for bringing about an inclusive data revolution and equips them with a broader perspective on the interplay between areas traditionally treated disparately in a STEM graduate curriculum.

The award is a culmination of efforts of many of my colleagues, including many not on this specific grant, to institutionalize novel research and education paradigms over several years, said project Principal Investigator and Professor Narayana Santhanam from the Department of Electrical and Computer Engineering in the College of Engineering. The grant will allow us to move in the direction of personalizing graduate instruction and allow students to see for themselves how seemingly different areas are interconnected. It will foster significantly closer research between different units and engage underrepresented groups in STEM, establishing long term mentoring structures that will persist beyond the life of the project.

Data science is becoming a core competency for many disciplines across UH Mnoa, said project co-Principal Investigator and Professor Philip Johnson from the Information and Computer Sciences Department in the College of Natural Sciences. This grant will allow us to explore novel ways to break down silos and facilitate multi-disciplinary research and education for our students.

The students will work in teams on fundamental and applied data science research on the following topics:

To solve pressing societal issues, we need to better understand and analyze human and social behavior backed by state-of-the-art data science, said project co-Principal Investigator and Professor Nori Tarui of the Department of Economics in the College of Social Sciences. With this grant, our interdisciplinary team of faculty members and students will work together with various partners toward practical, evidence-based solutions.

The program will also create outreach activities for Native Hawaiians, women and members of the military to broaden participation in the STEM workforce.

Traditional education programs have to consider the tradeoff between depthhow deep to cover conceptsand breadthhow many concepts and applications to cover, said project co-Principal Investigator and Assistant Professor June Zhang from the Department of Electrical and Computer Engineering. This grant will allow us to utilize novel educational tools like modules and knowledge bases to build a program that can offer students both depth and breadth in learning and research.

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$3M award boosts program developing well-rounded graduate data ... - University of Hawaii

Still in its early stages, one especially promisingapplication of AI in health is its use with population health data sets to help address the growth of chronic diseases. A session on Day Two of Digital Health AI and Data will focus on how AI can meet the challengesfaced by patients with multiple long-term conditions (MLTC).

Simon Fraser, professor of public health at the School of Primary Care, Population Science and Medical Education at the University of Southampton, has spent much of his career as a public health specialist looking at the epidemiology of long-term conditions.

He will join Dr Gyucha Thomas Jun, professor of socio-technical system design at the School of Design and Creative Arts at Loughborough, Krish Nirantharakumar, professor of health data science and public health at the University of Birmingham and Professor Michael Barnes, professor of bioinformatics and director of the centre for translational bioinformatics at Queen Mary, University of London for the AI and Data session, which looks at how four UK research groups are using AI and data analytics to look at Englands 14 million people living with MLTCs.

Fraser, who heads one of the National Institute for Health and Care Researchs (NIHR) seven research consortia looking at multiple long-term condition multimorbidity, observes that understanding the development of long-term conditions to better inform prevention requires information from across the life course, but that electronic health records are recent enough that they cannot provide sufficient information on their own.

We are exploring data that have the potential to look at the whole life course, Fraser told Digital Health News, adding that the research group is using both birth cohorts groups of several thousand people born in the same week in time (for example, in 1970), for whom extensive data is collected every few years and ordinary healthcare information in electronic health records.

Although social determinants of health, from upbringing to education to income, are known to influence the likelihood that an individual will develop health problems, that level of detail is often hard for researchers to access and such data is not routinely collected in health settings.

The important thing is to fill in that gap and bring those determinants into the wider story of development of long-term conditions across the life-course, Fraser said.

Because of the complexity of those data, there is the potential for AI methods to help with clustering, sequencing and various other aspects of how people develop conditions over time.

Using technology to create data links

Technology also has the potential to learn across datasets, for example between birth cohorts and routine healthcare records. In secure data environments, linkage is also possible between electronic health records and other valuable sources, such as educational and census data.

This linkage can help researchers learn without incurring the risk of identifying individuals. Ultimately, the goal is to learn at what periods in the life course it might be possible to intervene to prevent or delay the onset of multiple long-term conditions, he said.

There are challenges related to the very different data types we are using that only have some overlapping domains, he said. The birth cohorts are very rich in these social data and wider determinants, but relatively limited on the long-term condition front. The electronic health data records are rich on long-term conditions but relatively limited on social data.

The challenge for the future, Fraser said, will be finding new ways of looking across both kinds of data sets in ways that are both reliable and secure in order to give a fuller picture of the lifecourse.

AI and Data is from the organisers of the market-leadingDigital Health RewiredandDigital Health Summer Schoolsevents and includes a wide-ranging programme of events on two stages: AI and Analytics and Data and Research.

All sessions are CPD accredited. AI and Data is free for the NHS, public sector, start-ups, charities, education and research. Commercial tickets start from 275+VAT.Register here.

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AI and Data to look at use of data analytics to address long-term ... - Digital Health

This fall, fifteen new faculty members joined Bryant's community of scholars. The group is comprised of dedicated educators who are also accomplished researchers and industry leaders. Their acumen ranges from using data science to combat societal problems to reshaping how we see ourselves and society.

We are delighted to welcome new faculty members to Bryant community who bring a wealth of expertise, experience, and perspectives that I am quite certain will enrich our learning environment and inspire our students, says Provost and Chief Academic Officer Rupendra Paliwal, Ph.D. I am impressed by our new facultys dedication to teaching and the pursuit of knowledge, I know they will create a transformative experience for our students, and I am very much looking forward to our shared academic journey together.

These new faculty members, Paliwal notes, join Bryant at a time of growth and innovation. The universitys Vision 2030 Strategic Plan is ushering Bryant into a new era while supporting the universitys transformational learning experiences, exceptional outcomes, and mission to develop passionate, purpose-driven leaders. Cutting-edge academic programs launching this fall includeExercise and Movement Science, Arts and Creative Industries, and Healthcare Analytics, among others, alongside a new general education curriculum organized around the United Nations Sustainable Development Goals.

The following faculty members have joined Bryants College of Business, College of Arts and Sciences, and School of Health and Behavioral Sciences:

Barbara Byers, Lecturer of History, Literature, and the Arts, received her Ph.D. from the University of California. An accomplished scholar, performer, and manager, Byers is trained in vocal performance, composition, dance/physical theater, Oud, and several instruments, including the piano and guitar. Her dissertation, Helwalker, took the form of an experimental folk opera audio drama exploring nature, decay, and renewal in the context of a heros journey narrative structure. She received her M.A. from the University of California and her B.A. from Bates College.

Kristen Falso-Capaldi, Lecturer of History, Literature, and the Arts, is a writer, educator, filmmaker, and artist. She has previously taught at New England Institute of Technology and the University of Rhode Island, in the Cranston public school system, and as part of Bryants Writing Workshop course. Falso-Capaldi is the RI State Chair for Women in Film and Video of New England and was a speaker at this springs TEDxBryantU 2023. She received her B.A. in English and Communication Studies from the University of Rhode Island and her MAT in English and Education from Rhode Island College.

Geri Louise Dimas, Assistant Professor of Information Systems and Analytics,received her Ph.D. in Data Science from Worcester Polytechnic Institute and teaches both undergraduate and graduate data science courses. The Co-Director of the Institute for the Qualitative Study of Inclusion, Diversity, and Equity's (QSIDE) Stopping Trafficking and Modern-day Slavery Project (STAMP) Lab, her research focuses on applications of applied analytics and data science at the intersection of societal issues such as immigration, anti-human trafficking, and homelessness. She received her B.A. from Roosevelt University, and her M.S. from Bowling Green State University.

Amanda Fontaine, Assistant Professor of Politics, Law, and Society, holds a Ph.D. from the University of New Hampshire. Her dissertation examined the interplay of personality, social support, and sociodemographics on college students mental health. Her current work involves the dissemination of peer-reviewed and evidence-based suicide prevention research/practices. Fontaine also received a Cognate in College Teaching, an M.A. in Sociology, and an M.A. in Music Studies from the University of New Hampshire, as well as a B.A. in Psychology and Music Theory/Composition from Clark University.

Mary Ann Gallo, Lecturer of Communication and Language Studies, has taught at New England Institute of Technology, Community College of Rhode Island, the University of Rhode Island, Johnson and Wales University, Nichols College, and Roger Williams University. She has also taught several Communications courses at Bryant, including Intro to Communication, Public Speaking, Public Relations, and Interpersonal Communication, and has also worked as a freelance writer, information and public relations specialist, and news reporter/anchor at different points during her career. Gallo received both her B.A. and her M.S. from Northeastern University.

Yuan Guo, Visiting Assistant Professor of Information Systems and Analytics, received his Ph.D. from Northeastern University. His industry experience includes serving as a machine learning engineer for LZ Finance and as a senior software engineer at Baidu Research USA, a research and development center for Baidu, Chinas largest search engine provider. Guos research has been published and presented in a number of different publications and forums. He received his M.A. in electrical engineering from Tsinghua University and his B.Sc. in electronics engineering from Huazhong University of Science and Technology.

Eun Kang, Associate Professor of Marketing, received her Ph.D. from the University of Texas at Austin. She has previously taught at Kutztown University of Pennsylvania and the University of Texas at Austin. Kangs research interests include digital marketing, influencer marketing, consumer psychology and behavior, and sustainability and ethical consumption and her published work ranges from the motivations for binge watching to how advertising has affected alcohol sales. Kang received an M.A. and B.A. from Michigan State University and two B.S. degrees from Kyung Hee University.

Carrie Kell, Lecturer of History, Literature, and the Arts, received her Ed.D. in Learning, Design, and Technology from the University of Wyoming. Her teaching philosophy is founded on student-centered teaching strategies and she has taught at the University of Toledo and the University of Rhode Island, among other schools. She has also served in a range of capacities at Rhode Island School of Design, Middlebridge school, and several other learning institutions. Kell earned her M.Ed. from Northwestern University, and an M.A., B.E., and B.A. from University of Toledo.

David Liao, Lecturer of History, Literature, and the Arts, earned his Ph.D. from Brown University. His research and teaching interests include multiethnic U.S. literatures, comparative race and ethnic studies, twentieth and twenty-first century U.S. literature and culture, histories of dictatorship and authoritarianism, twentieth century discourses of memory, and genre fiction. Liaos scholarly work includes examinations of the role the film Scarface has played in the evolution of hip-hop, the Godfather trilogy, and the fiction of John LeCarre. He received his B.A. from the State University of New York at Binghamton.

Melanie Maimon, Assistant Professor of Psychology, earned her Ph.D. in Social Psychology from Rutgers University-New Brunswick. Her research examines the experiences and consequences of stigmatization and explores methods to improve the inclusion and belonging of people with minoritized identities across social environments. While completing her doctoral degree, Maimon worked with the TA Project at Rutgers University, leading inclusive teaching workshops and courses on teaching in higher education. Maimon earned her M.S. from Rutgers University-New Brunswick and her B.S. from the University of Massachusetts-Amherst.

Taylor Maroney, Lecturer of History, Literature, and the Arts, received their MFA in painting from the University of Massachusetts Dartmouth. They have been teaching nationally and internationally since 2010 in various environments and student demographics from South Africa to San Francisco to rural North Dakota. Their research focuses on race and gender constructs within the United States and their work has been featured in multiple publications and exhibitions. Maroney also received their M.A. from University of Massachusetts Dartmouth and their BFA from the University of New Hampshire.

Eric Paul, Lecturer of History, Literature, and the Arts, received his MFA from Farleigh Dickinson University. He has previously taught at Johnson and Wales and Dean College, as well as various Bryant University courses. Paul's work has been published in a variety of publications as well as several collections of his poems 2019's A Suitcase Full of Dirt being the most recent an audiobook, and a vinyl spoken word release. He has also served as the poetry editor for the three most recent volumes of the university's Bryant Literary Review. Paul received his B.A. from Rhode Island College.

Nafees Qamar, Associate Professor and Healthcare Informatics Director, received his Ph.D. from the University of Grenoble. With a comprehensive background spanning health informatics, applied computer science, and software security, Qamar is dedicated to bridging the gap between healthcare and technology to enhance patient care and data management. Over the course of his career, Qamar has held distinguished positions at a variety of institutions, including the State University of New York and Vanderbilt University, which has aided him in nurturing a multidisciplinary perspective. Most recently, he served as an associate professor at Governors State University in Chicago.

Jerrica Rowlett, Assistant Professor of Communication and Language Studies, received her Ph.D. from Florida State University. Rowletts research explores the intersection of a range of topics including gender, politics, pop culture, and social media and her dissertation explored the role Snapchat Live Stories has played in the collective identity and action of offline communities. She has previously taught as an assistant professor of Communication and Media Studies at Georgetown College. Rowlett received her M.A. from Clemson University and a B.A. from Georgetown College.

Jason Sawyer, Associate Professor and Exercise and Movement Science Program Coordinator, received his Ph.D. from Springfield College. He has previously taught at numerous institutions, most recently Rhode Island College. An accomplished scholar and presenter, Sawyers research interests have recently focused on the effects of exercise on depression in college-aged individuals. He has previously served as the Rhode Island state representative for the National Strength and Conditioning Association, and his coaching experience includes strength and conditioning, Olympic weightlifting, basketball, and martial arts. He received his B.S. from Plymouth State University and his M.S. from Springfield College.

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Bryant welcomes 15 new faculty members to the university community - Bryant University