Giving Thanks Where Thanks is Due

One of the great joys of being the Director of the National Library of Medicine is the many opportunities for me to express gratitude. In the past, I have given thanks to NLM staff who are veterans (2021), for progress during my tenure (2020), and to our amazing NLM staff members (2019). This year, I am pausing to give thanks for the outstanding products and services developed and stewarded by our NLM staff, made available every day of the year to anyone with an internet connection—and even to some without!

First, I am thankful for our information collections in their many forms. The NLM Board of Regents oversees our Collection and Preservation Policy, which guides NLM as it meets its mission to acquire, organize, preserve, and disseminate biomedical knowledge from around the world. Our collection spans ten centuries from the 11th to the 21st, and ranges from the third oldest Arabic medical manuscript in existence to the “Rosetta Stone” of modern science, Marshall Nirenberg’s genetic chart, from genomic sequences essential for current and future research to information for mothers taking care of sick children.

Organizing the collections and making them findable and accessible builds on the knowledge of library and information science. This foundational knowledge means we can tag objects—real or virtual—with codes and terms that help with organization and retrieval. It also means we use our knowledge of library and information science to guide efforts to annotate and curate molecular data, literature citations, and images so they are accessible to the public. So I am grateful not only for the 66 miles of shelving that hold our precious objects, books, and journals here in Bethesda, but for the ever-powerful computer clouds that preserve our high-value research databases and 34 million bibliographic citations in PubMed. Libraries do more than house books; they use sophisticated knowledge to organize materials and make them readily available.

I am thankful for the ways that staff at NLM’s National Center for Biotechnology Information (NCBI) manages the submission, curation, and dissemination of our enormous genomic and molecular databases. From ClinVar (our collection of genomic sequences linked to clinical annotation) to the Sequence Read Archive (the world’s largest scientific data repository), our staff makes sure that depositors can effectively deposit data, scientific curators can conduct quality checks, and web and interface designers allow access to the data. A few years ago, the NCBI team led a cloud migration process to make available data from the entire 15-petabyte SRA resource on two commercial cloud providers. This bold step democratized sequence-based scientific inquiry and harnessed the computational power of cloud platforms, which contributed to industrial innovations and shortened the pathway for scientific discovery from days and months to minutes and hours. I am thankful for the role NLM plays in accelerating scientific advances and leveraging research resources for public health benefit.

NLM offers more than 1,000 easy-to-read health topic articles through our online consumer health information resource known as MedlinePlus. MedlinePlus is available in both English and Spanish, thereby assuring information access to speakers of two of the world’s most common languages. Through MedlinePlus Connect, our technical team also provides direct, tailored access to MedlinePlus resources automatically through electronic health records, patient portals, and other health information technology systems to deliver information from MedlinePlus to patients and providers at the point of care. I am thankful for the efforts of the MedlinePlus teams that bring timely and trusted information to the lives of everyone, everywhere.

I hinted earlier that there are two main pathways to access NLM products and services. Electronic access, supporting both human- and machine-readable forms, is by far the most common pathway to NLM. We also support the Network of the National Library of Medicine (NNLM) and its more than 8,000 members around the country in public, hospital, and academic medical center libraries to bring the power of NLM and its resources to the public. I am grateful for everyone who works as part of NNLM for their ability to bring NLM’s products and services to communities everywhere as well as how the needs and practices of those communities bring awareness of NLM.

As you pause this year in thanksgiving for the many public services that support you in everyday life, please remember to give thanks for NLM’s products and services. We think they are world class, and we are grateful for our ability to serve you.

NLM is Celebrating 40 Years of Biomedical Training

Guest post by Richard C. Palmer, DrPH, JD, Acting Director, Division of Extramural Programs, National Library of Medicine (NLM), National Institutes of Health (NIH).

This summer, NLM is marking its 40th year of supporting Biomedical Informatics and Data Research Training (T15). This is an amazing accomplishment, and I extend my congratulations to all the past and present institutional training grant directors, trainees, and NLM staff that have helped mature the field, grow the scientific workforce, and prepare this country for a biomedical revolution. This revolution harnesses the power of data to improve scientific exploration, clinical care, public health practice, and personal health.

Although almost 40 years have passed, NLM is more committed than ever to support career training, which is a central component of the NLM Strategic Plan. Recently, NLM released a new R25 program focused on supporting innovative educational programs and research experiences aimed at preparing talented and diverse students for future careers in biomedical informatics and data science. NLM also recently awarded 18 T15 grant awards, the largest number of awards made to date, to help ensure an available data-driven biomedical informatics and data science workforce. About 170 graduate and postdoctoral students will be trained annually by the T15 program to meet this growing workforce demand. NLM recognizes that we need to invest in training to ensure that a well-trained informatics and data science workforce exists to address the health needs of this nation.

Personally, I am amazed with just how fast the biomedical informatics and data science field has grown in the past 10 years. I entered this field with a study that aimed to build a clinical decision support tool to help manage fall risk for older adults—I vividly remember the headache associated with the interoperability (a computer or software inability to exchange and utilize data or other information) of data sources. Since then, I have witnessed rapid change occurring—due in part to the continued advances in computing, data storage, and standardization—that has allowed biomedical informatics to quickly advance. This change is occurring rapidly. To harness this acceleration in the acquisition, storage, retrieval, and use of information in health research and for the biomedical enterprise, we need a highly skilled workforce, and the demand for scientists trained in these areas and who can apply these skills to health and biomedicine is higher than the current supply. NLM’s commitment to training is helping ensure that a workforce capable of leading innovation exists.

Since joining NLM, I have had the opportunity to learn more about NLM’s T15 training program and the impact it’s had. Forty years is a long time, so I pieced together data to identify a common trend: The majority of the T15 trainees move on to research-oriented roles in academic institutions, not-for-profit research organizations, governmental and public health agencies, pharmaceutical and software companies, and health care organizations. Those in training over the past 10 years published 2,350 articles, with nearly 23% of these publications being highly cited, and were associated with 23 patents. In addition, T15 trainees are taking on leadership roles in academia, health centers, and research organizations. Even NIH’s own Dr. Josh Denny, who leads the All of Us program, and Dr. Michael Chiang, Director of the National Eye Institute, are former T15 trainees.

Just recently, I was able to participate in my first T15 trainee conference hosted by the University at Buffalo, SUNY and saw what research T15 trainees were involved with. What impressed me was the passion these trainees had for the science and their commitment to tackling pressing biomedical issues. Trainees are conducting research in areas including basic biomedical research, health care delivery, clinical and translational research, public health surveillance, and consumer health. Given their level of engagement, there is little doubt that many current T15 trainees will build successful scientific careers that will benefit society tremendously. At NLM, we are committed to training and fostering the development of the next generation of biomedical informatics and data scientists and look forward to the scientific advances they make. They say time flies when you’re having fun, and the last four decades sure have flown by. Here’s to another 40 years of NLM-supported training!

Dr. Palmer oversees NLM’s grant programs for research, resources, workforce development, and small business related to biomedical informatics and data science. Prior to joining NLM, Dr. Palmer was a Health Scientist Administrator at the National Institute on Minority Health and Health Disparities. He has over 25 years of extramural research experience and has been an investigator on NIH and CDC funded research grants. Dr. Palmer has conducted research in health care and community-based settings aimed at addressing health disparities, understanding health care decision-making, and improving health outcomes and disease management among older adults.

Want to learn more about NLM’s support for training?

View a panel discussion on Lindberg and the Advancement of Science through Research Training held during the 2022 Lindberg-King Lecture and Scientific Symposium: Science, Society, and the Legacy of Donald A.B. Lindberg, MD on September 1. The panel addressed the leadership of Dr. Donald A.B. Lindberg, former NLM director, in the advancement of science through research training with emphasis on the field of informatics.

Meet the NLM Investigators: Dr. Demner-Fushman Knows the Answers to Your Questions!

Meet my close colleague, Dr. Dina Demner-Fushman! This brilliant researcher is the face behind what many of you have already accessed on NLM’s websites. Many of you will agree with me when I say that having one PhD is extremely impressive–but would you believe she has TWO?! In addition to her master’s degree, Dr. Demner-Fushman has PhDs in immunology and computer science.

Dr. Demner-Fushman and her team use advanced artificial intelligence (AI), natural language processing, and data mining techniques to answer consumers’ questions about a variety of health topics. Did you know that it was Dr. Demner-Fushman’s research that led to the developmental stages of the indexing initiative that produced the current iteration of the MEDLINE resource? This work helps all of us navigate a plethora of NLM resources.

Check out the infographic below to learn more about the innovative, important research happening in Dr. Demner-Fushman’s lab.

Infographic titled: Biomedical Question Answering. The title area features a picture of Dr. Demner-Fushman along with her title and accreditations (MD, Phd): Investigator, Computational Health. The first column of the graphic explores her short and long-term goals  for her projects. The center column describes the processes she uses to achieve these goals, and the last column depicts a simple graphic illustrating a Q and A service.

What makes your team unique? Tell us more about the people working in your lab.   

It is a diverse, multicultural team. Some were even born after I got my first IT job checking computers at Hunter College for Y2K compliance. The team is united by the task of enabling computers to understand health-related information needs and the socioeconomic and professional status of people who come to NLM seeking information. It is a group of exceptionally dedicated and talented people. Our diverse backgrounds make us see all possible aspects of addressing the informational and emotional needs of our users. 

What is your advice for young scientists or people interested in pursuing a career in research?  

  • Be proactive: Seek information and take advantage of training opportunities.  
  • Be brave: Admit you don’t know or don’t understand something. Most people will try to help.  
  • Be bold: Reach out to people who you would like to work with or to discuss your ideas.  
  • Be honest.  
  • Be patient: Research implies working hard, sometimes without immediate results. Even if research is your passion and fun, sometimes you have to do things that you might not enjoy or you might fear but still have to do, like giving talks or writing paper.

What do you enjoy about working at NLM?  

The community of dedicated people across all divisions, the mission, and the intellectual freedom.  

Where are you planning to travel to this year?  

I was just in Dublin, Ireland, in May for the 60th meeting of the Association for Computational Linguistics and co-chaired the BioNLP workshop for the 15th time. I loved Dublin when I visited shortly before the pandemic. I enjoyed revisiting a place I loved and discovering new things to love.

What are you reading right now?  

In the Garden of Beasts by Erik Larson. It provides an amazing view of pre-World War II Germany and political relations. I hope some lessons have been learned! 

You’ve read her words, now hear them for yourself. Follow our NLM YouTube page for more exciting content from the NLM staff that make it all possible. If you’d like to learn more about our Intramural Research Program (IRP), view job opportunities, and explore research highlights, I invite you to explore our recently redesigned NLM IRP webpage.

Transcript [Demner-Fushman]*: When people need information, what they really like is to ask a question and get a really good comprehensive answer, and to also know that the answer is true and correct.

When I started my independent clinician career, I had lots of questions, but I was sometimes not even sure if I was getting the right answer. “Question answering” is this system to understand the question, what the question is about, and why it is asked. When the answer is found, it’s usually not a single answer: It’s parts of the answer in different places. It’s multiple answers. So, all of that then needs to be condensed into one comprehensive answer with evidence of where the answer came from. So that’s the focus of my research.

On the surface, very similar questions asked by clinicians and by the public should be answered very differently. Different deep-learning systems are needed to find the answers to the same question asked by two different people.

The long-term goal is one entry point to all the NLM resources. It doesn’t matter who the person is and how they ask their question or look for information. We should be able to recognize what the person needs and provide it. There is no one—other than NLM—who is specifically dedicated to biomedical information retrieval and biomedical question answering. Although it seems industry is doing that kind of research as well, it is not their main focus, whereas we keep people focused on what really matters for health and advancing medicine.

*Transcript edited for clarity

Meet the NLM Investigators: For Sameer Antani, PhD, Seeing is More Than Meets the Eye

It’s time for another round of introductions! Many of you may already know Sameer Antani, PhD—one of NLM’s most decorated and prestigious investigators—from his many awards and accolades. In March 2022, he was inducted into the American Institute for Medical and Biological Engineering’s College of Fellows, an impressive group that represents the top two percent of medical and biological engineers. This distinction is one of the highest honors that can be bestowed upon a medical and biological engineer. Can you tell we are proud of him?!  

We selected Dr. Antani to join our NLM family after a nationwide, competitive search, and his genius was readily apparent from the start. Dr. Antani’s career spans over two decades, during which he developed an innovative research portfolio focused on machine learning and artificial intelligence (AI). His lab at NLM focuses on using these tools to analyze enormous sets of biomedical data. Through this analysis, AI technology can “learn” to detect disease and assist health care professionals provide more efficient diagnoses. Examples of Dr. Antani’s work can be found in mobile radiology vehicles, which allow professionals to take chest X-rays and screen for HIV and tuberculosis using software containing algorithms developed in his lab. Check out the infographic below to learn more about the exciting research happening in Dr. Antani’s lab.

Infographic titled: Seeing is more than meets the eye. Under the title the investigator's name, title and division are listed as: Sameer Antani, PhD, Investigator, Computational Health. 

The first column of the infographic is titled: Projects. Two bullets are listed in the first column. The first bullet reads: Discovering the impact of data on automated AI and machine learning (AI/ML) processes on diagnostics. The second bullet says: Improving AI/ML algorithm decisions to be consistent, reproducible, portable, explainable, unbiased, and representative of severity.

The second column is titled: Process. The first bullet in this column reads: Using images and videos alongside AIML technology to identify and diagnose:
Cancers: Cervical, Oral, Skin (Kaposi Sarcoma)
Cardiomyopathy 
Cardiopulmonary diseases. 
The second bullet reads: Analyzing a variety of image types, including:
Computerized Tomography (CT), Magnetic Resonance Imaging (MRI), X-ray, ultrasound, photos, videos, microscopy. 

The third and final column in the infographic is titled: What It Looks Like. In this column there are four images of chest x-rays illustrating the detection of HIV and TB.

Now, in his own words, learn more about what makes Dr. Antani’s work so important!

What makes your team unique? Tell us more about the people working in your lab.   

The postdoctoral research fellows, long-term staff scientists, and research scientists on my team explore challenging computational health topics while simultaneously advancing topics in machine learning for medical imaging. Dr. Ghada Zamzmi, Dr. Peng Guo, and Dr. Feng Yang bring expertise and drive to our lab. The scientists on my team, Dr. Zhiyun (Jaylene) Xue and Dr. Sivarama Krishnan Rajaraman, add over two decades of combined research and mentoring experience.  

What do you enjoy about working at NLM?  

There are many positives about working at NLM. At the top of the list is the encouragement and support to explore cutting-edge problems in medical informatics, data science, and machine intelligence, among other initiatives. 

What is your advice for young scientists or people interested in pursuing a career in research?  

I urge young scientists to recognize the power of multidisciplinary teams. I would also urge them to develop skills to clearly communicate their goals and research interests with colleagues who might be from a different domain so they can effectively collaborate and arrive at mutually beneficial results. 

Where is your favorite place to travel?

I like to travel to places that exhibit the natural wonders of our planet. I hope to visit all our national parks someday. 

When you’re not in the lab, what do you enjoy doing?

I am studying and exploring different aspects of music structure.

You’ve read his words, and now you can hear him for yourself! Follow our NLM YouTube page for more exciting content from the NLM staff that make it all possible. If you’d like to learn more about our IRP program, view job opportunities, and explore research highlights, I invite you to explore our recently redesigned NLM IRP webpage.

YouTube: Sameer Antani and Artificial Intelligence

Transcript: [Antani]: I went to school for computer engineering in India. I’ve worked with image processing, computer vision, pattern recognition, machine learning. So my world was filled with developing algorithms that could extract interesting objects from images and videos. Pattern recognition is a family of techniques that looks for particular pixel characteristics or voxel characteristics inside an image and learns to recognize those objects. Deep learning is a way of capturing the knowledge inside an image and encapsulating it, and then researchers like me spend time advancing newer deep-learning networks that look more broadly into an image, recognizing these objects—recognizing organs, in my case, and diseases—and converting those visuals into numerical risk predictors that could be used by clinicians.

So my research is currently in three very different areas. One area looks at cervical cancer. A machine could look at the images and be a very solid predictor of the risk to the woman of developing cervical precancer, encouraging early treatment. Another area I work with [is] sickle cell disease. One of the risk factors in sickle cell disease is cardiac myopathy or cardiac muscle disease, which leads to stroke and perhaps even death. Looking at cardiac echo videos and using AI to be a solid predictor, along with other blood lab tests, improves the chances of survival.

A third area that I’m interested in is understanding the expression of tuberculosis [TB] in chest X-rays, particularly for children and those that are HIV-positive. The expression of disease in that subpopulation is very different from adults with TB who are not HIV positive. Every clinician has seen a certain number of patients in their clinical training. They perhaps have spent more time at hospitals or clinical centers, been exposed to a certain population, and they become very adept at that population. Machines, on the other hand, could be trained on data that is free of bias, from different parts of the world, different ethnicities, different age groups, so that there’s an improved caregiving and therefore, a better expectation on treatment and care.

Note: Transcript was modified for clarity.

MLA ’22: NLM as an Engine for Innovation and Discovery

Guest post by Amanda J. Wilson, Chief of the NLM Office of Engagement and Training (OET), and Dianne Babski, Associate Director for Library Operations.

NLM is excited to participate in the annual Medical Library Association (MLA) conference MLA ’22: Reconnect, Renew, Reflect, held virtually from April 27 to May 2 and on-site in New Orleans from May 3 to 6.

Information on how NLM products, services, and programs support innovation and discovery is available at NLM @ MLA’22. We encourage to you visit the NLM Technical Showcases on May 5 for a PubMed update with Amanda Sawyer, an introduction to NIH Data Management and Sharing Policy from Dr. Lisa Federer, and a PubMed Central update and information about NIH preprints with Katie Funk. The NLM Update on May 6 with Dianne Babski, Amanda Wilson, and Network of the National Library of Medicine (NNLM) Project Director Martha Meacham will include the latest activities and be followed by an interactive Q&A.

If you missed the April 28 session, check out the NNLM Day @ MLA: National Update page to hear about NNLM members’ work and accomplishments over the past year and to learn how the regions took advantage of their new configuration, partnerships, upcoming activities, and available opportunities. For example, the NNLM Center for Data Services hosted a session to help professionals implement the NIH Data Management and Sharing Policy, with concurrent sessions from the NNLM Training Office and NNLM Public Health Coordination Office. NNLM Day will reconvene in November 2022, so be sure to let us know your topics of interest.

MLA, which comprises more than 400 institutions and 3,000 professionals, is one of NLM’s key stakeholder groups that inform our products, initiatives, and services. MLA’s annual meeting offers NLM the opportunity to introduce new products and initiatives, get feedback on our services, and explore ways to better support the medical library community. As an NIH institute and a national library, NLM continually adapts to changes in the research ecosystem, including data standards, scientific developments, technological advancements, and the evolving norms of how we operate together.

As a catalyst for innovation and discovery, NLM is committed to equipping health science information professionals and the public at large with tools, platforms, and the ability to conduct today’s data-intensive research and community outreach. Please visit NLM @ MLA’22 to learn how you can become part of this partnership as we develop health information solutions and joint programs to support the future of health information.

Ms. Wilson coordinates engagement, training, and outreach staff from across NLM to elevate NLM’s presence across the United States and internationally. OET is also home to the Environmental Health Information Partnership for NLM and coordinates the Network of the National Library of Medicine.

Ms. Babski is responsible for the management of one of NLM’s largest divisions, with more than 450 staff, who provide health information services to a global audience of health care professionals, researchers, administrators, students, historians, patients, and the public.

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