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)
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.

Meet the NLM Investigators: L. Aravind Iyer, PhD, Uncovers the Language of Our DNA

NLM is home to a robust research enterprise. Before the COVID-19 pandemic, I introduced you to two researchers from our Intramural Research Program (IRP), Dr. Lauren Porter and Dr. Xiaofang Jiang.

Now I would like you to meet another one of our researchers, L. Aravind Iyer, PhD. A member of the NLM IRP, Dr. Iyer is a Senior Investigator in the Computational Biology Branch of the National Center for Biotechnology Information. His research revolves around uncovering the stories and patterns held within DNA and RNA and is aimed at unraveling the evolutionary forces that shape biochemical functioning and biological form.

Just like any other biological structure, DNA and RNA evolve over time, which can tell a complex story of an organism’s past and illustrate relationships between organisms that aren’t obvious.

See the infographic below to learn more about the exciting research happening in Dr. Iyer’s lab.

Infographic titled: Language of Our DNA and RNA. Listing the featured researcher, L. Aravind Iyer, PhD and his title, Senior Investigator in Computational Biology. 

The first column of the infographic reads: What I'm Working On. The text in the first column lists Dr. Iyer's short term goals to: (1) Decipher evolutionary relationships of organisms (vertical and lateral) and proteins; and (2) Computationally discover biochemical activities of proteins. Next, long term goals are listed as: (1) Create a unified evolutionary theory for biological conflicts; and (2) Understand the contributions of rapid evolution in conflict on other systems.

The second column is titled: How It Works and lists the following text: (1) Reading an evolving story written in DNA/RNA and protein sequences.

(2) Closing gaps in our understanding by applying computational and statistical methods on databases to compare protein sequences and structures.

(3) Determine vertical (ancestral with a picture of an arrow pointing to  descendant) and lateral (one organism with a picture of an arrow pointing to another organism) flow of genetic information.

The third and final column of the infographic is titled: What It Looks Like and has a book in an indecipherable language with a caption that says: Deciphering the language of life written in DNA/RNA and protein sequences.

Now, in his own words, learn more about the man behind the research!

What do you enjoy about working at NLM?
NLM is one of the world’s leading centers (such can be counted on one’s fingers) for deciphering the biochemistry and biology of proteins through computational analysis of sequences and structures. As a national lab, it has an organizational structure and funding framework best suited for the kind of research that I do, which involves an extensive explorative component.

What makes your team unique?
My team embodies a considerable mass of special knowledge regarding protein evolution and function that we accumulated and systematized over a period of several decades. Given that we look at this using various computational methods, my team melds the expertise of people well versed in biology, computer programming, biochemistry, protein structure, and graph-theoretic analysis.

What is your advice for young scientists or people interested in pursuing a career in research?
I think the most interesting discoveries are those that bring together and illuminate disparate areas of inquiry. Hence, spend your early youth acquiring a very diverse knowledge base and technical capacity. Then organize this knowledge into an interconnected network that you can train your intuition on and draw from when confronted with new problems.

When you’re not in the lab, what do you enjoy doing?
Amateur astronomy, reading and writing about history and ancient texts in the original or translations, recreational mathematics, storytelling.

What inspires you?
Lives of past scientists, philosophers, and leaders from around the world. The profound insights found in the works of the ancients.

You’ve read his words, but now you can hear them for yourself. Follow along on the NLM YouTube page for more exciting content from the NLM staff that makes 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 the newly redesigned NLM IRP webpage.

YouTube: Dr. Aravind Iyer and the Protein Universe

Video transcript

[Iyer] Early in my life, I wanted to be a paleontologist. And that’s what actually led me to molecular biology. At one level, I could say that I wish to understand the whole protein universe. Proteins can be divided into evolutionary units. There’s a part of a protein that’s preserved over evolution because natural selection is maintaining that part for some reason. And one realization, which dawned on us starting around the early nineties—and this was a very profound realization for all of biology—is that there is a relatively small number of these evolutionary units of proteins, which we term domains, which constitutes the entire protein universe of all organisms across the tree of life.

If we can understand the functions of these units, then that goes a long way towards understanding what organisms do. And given there are many gaps in our understanding of what organisms do, one way to get at it is to first, find all these domains. The second aspect of it is predicting functions for them. The first phase of my research, we captured most of the low-hanging fruit, which were the big families conserved across all organisms.

Now we are moving on to the more difficult terrain, but the difficult terrain also holds a lot of promise because many un-understood functions are hiding within that difficult terrain, and it gives these offshoots in the form of biotechnological reagents. There are things like restriction enzymes, the CRISPR systems, and DNA modification systems. All of these have become very popular reagents.

NLM is a world leader in the analysis of protein sequences, protein structures, and inferring evolution from these bits of information. And this has been a very long-standing interest of mine so, this is the place to be.

The World is Waking Up

One of my favorite books is the first of C.S. Lewis’ Chronicles of Narnia, The Lion, the Witch and the Wardrobe. This book talks about the forest re-awakening to greet a new world, and names are returned to all creatures of the forest.

This is particularly relevant to NLM, where we employ health data standards to ensure that experiences related to health and illness have trustable and commonly used terms that allow health information in one context to be easily communicated in another… think of helping the clinicians at a receiving hospital understand the health concerns of a patient that is being transferred from a different facility.

But that’s not what this story is about – it’s about bringing the people who create these health data standards, and those who use them, back to work! Really, we’ve never been away from work. I am incredibly proud of the fact that NLM staff have continued to bring our valuable services and offerings to all those who need them despite being on a maximum telework status. Each month when we meet for our all-staff virtual NLM Town Hall meetings, I start by thanking our staff for their efforts to make sure that our valuable NLM resources remain available to the public.

Now, following the second anniversary of the COVID-19 pandemic, we are getting ready to return to the physical workspace. Between now and early May, we will be returning most of our NLM staff to the physical workspace.  

What does this mean? Well, I will give you a sneak peek… since last December, five members of our NLM leadership team have been going into the physical workspace. I asked these colleagues to commit to coming into the office for 5 hours every Tuesday. So, around 9:30 am every Tuesday, we (me, our Deputy Director, Executive Officer, Acting Scientific Director, and Operations Coordinator), properly masked and distanced, meet in the Executive Conference Room. I have to say that there is a peculiar delight in us all being together! For the remainder of the day, we all work safely in our offices, gathering as appropriate for meetings among the five of us or across our entire leadership team using virtual platforms!

Over the next few weeks, we will be inviting the rest of NLM staff back to the physical workspace, but it won’t be to the way it used to be. We will be learning together about the future of work.

Our leadership team has been hard at work examining the functional statements of each division and evaluating how each division meets it mission to contribute to NLM’s greater mission and vision. Our leadership team is working to decide how every position contributes to the NLM vision, and to determine how much flexibility, in location and working hours, may be afforded to each position and to the working groups in which those positions are situated. Following this, our directors will work with their supervisors and managers to engage with each staff member to create the best arrangement that advances the NLM mission in a manner that is fair to everyone and affords the maximum feasible workplace flexibilities for all. 

Come along with us as we define the new normal – the NLM of the future! I have commissioned the NLM Future of Work Working Group to help us envision what the professional world will become to ensure that NLM continues to serve scientists and society. How can we serve you?

How to be an Ally for Change

Guest post by Marguerite Matthews, PhD, a Program Director in the NIH National Institute of Neurological Disorders and Stroke, Office of Programs to Enhance Neuroscience Workforce Diversity, and Maryam Zaringhalam, PhD, a Data Science and Open Science Officer in the NLM Office of Strategic Initiatives.

Almost a year ago, the NIH UNITE initiative launched in response to resounding calls for racial equity across the country and within the NIH community. The Centers for Disease Control and Prevention also released a statement signifying that racism “negatively affects the mental and physical health of millions of people, preventing them from attaining their highest level of health, and consequently, affecting the health of our nation.” Taking to heart the urgent need for change, our colleagues across UNITE’s five committees have spent the last year developing recommendations, programs, and infrastructure for NIH to advance its commitments towards racial equity.

Still, we recognize that there are staff across NIH who have yet to engage in NIH’s efforts to combat structural racism, which centers on policies, practices, and culture that perpetuate inequities based on the social construction of race. We cannot passively wish away those structures for, as Martin Luther King, Jr. noted, “He who passively accepts evil is as much involved in it as he who helps to perpetrate it.” Instead, we must actively engage in dismantling those policies, practices, and cultures.

Structural racism is distinct from interpersonal racism between individuals, which often comes to mind when we hear the word “racism.” Structures that perpetuate racial inequities continue to exist whether individuals are interpersonally racist or not. For an example of structural racism’s effects, look no further than the COVID-19 pandemic. The disease’s disproportionate impact among racial and ethnic minority groups has cast a light on long-standing health disparities.

Figuring out how to reshape long-standing structures can be intimidating, but if the pandemic has shown us anything, it’s that we have a profound capacity for transformational change. Whether or not we are in formal supervisory or leadership positions, we all have the power to influence those around us — and that influence ripples out.

How We can Act as Allies and Champions for Change  
  • Act as a force multiplier in conversations around structural racism to build consensus that it is a real and pressing problem, and we all have a role to play in uprooting it. Research has demonstrated that when members of marginalized groups discuss unfair treatment in the workplace, they are penalized with worse performance ratings for doing so.
  • Be intentional about creating a workplace where everyone is valued, their roles appreciated, and their perspectives recognized. Actively taking steps to foster a more inclusive environment where staff are afforded equitable access to opportunities will ensure we are retaining talent, while also attracting new staff and setting them up for success.
    • Acknowledge and amplify your colleagues’ contributions. This action can also help elevate their visibility in the workplace, which is particularly important given research that shows, for example, statements made by Black women in group discussions are less likely to be correctly remembered or attributed to them.
    • Create channels for communication for you and your colleagues to share ideas, feedback, or needs. A report from the Catalyst found 60 percent of Asian, Black, Hispanic/Latinx, and multiracial professionals surveyed feel on guard and mentally prepared to protect themselves against bias. This emotional tax can interfere with a strong drive to contribute, so intentionally designed communication strategies can lower barriers for staff to feel comfortable engaging.
    • Work with your colleagues to create spaces for people to express themselves, co-creating expectations for how to engage, practicing civility, and extending grace. Doing so is an opportunity to ask your colleagues what they need to fully participate in workplace discussions and recognizing everyone is experiencing unique circumstances and challenges.
  • Practice being an upstander and promoting positive and civil behaviors among colleagues. Research shows that in the presence of others, an individual may be discouraged from intervening in an emergency situation (such as harassment or bullying), known as the bystander effect. Silence is complicity. Therefore, when you see micro– or macro-aggressions, discrimination, or the perpetuation of stereotypical beliefs, make the choice to intervene and hold your colleagues accountable for their actions. NIH provides bystander intervention training to help employees to create a culture in the workplace and beyond where harassment and bias incidents are less likely to occur.
  • Move towards a culture of harm prevention. Show respect for your colleague’s racial and cultural differences and refuse to participate in or condone discrimination and harassment. When colleagues exhibit harmful behaviors – whether intentionally or unintentionally – explain why their behavior is unacceptable and consider helping them develop strategies to prevent them moving forward.
  • Evaluate the working groups, committees, and councils of which you are a member. Ask what experiences and expertise are missing and advocate for new membership or guest experts to fill these gaps. Diversity enhances creativity and problem-solving. Furthermore, engaging and centering the experiences of staff from historically marginalized racial and ethnic groups can embed equity and justice in the programs, policies, and research we support.

These suggestions are just a starting point and can serve as the basis for creating an anti-racist community of practice with both your colleagues and acquaintances beyond the workplace, sharing constructive actions to address racial inequities in our daily lives. For more ideas on how to join this work, visit UNITE and 8 Changes for Racial Equity at the NIH (8CRE).

Dr. Matthews earned a PhD in neuroscience at the University of Pittsburgh and completed a postdoctoral fellowship in behavioral neuroscience at the Oregon Health & Science University before coming to the NIH as an American Association for the Advancement of Science (AAAS) Science & Technology Policy Fellow. She serves on the UNITE “I” Committee, which is focused on improving NIH’s internal culture, and is a member of 8CRE.

Dr. Zaringhalam is responsible for monitoring and coordinating data science, and open science activities and development across NLM, NIH, and beyond. She completed her PhD in molecular biology at Rockefeller University before joining NLM as an AAAS Science & Technology Policy Fellow. She serves on the UNITE “E” Committee, which is focused on the extramural research environment.

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