How Mount Sinai is Transforming Care for Patients with Brain, Spine, and Central Nervous System Disorders

Updated on Nov 19, 2025 | Artificial Intelligence, Featured

Mount Sinai’s departments of Neurology and Neurosurgery are committed to innovation for the treatment of disorders of the brain, spine, and central nervous system. That commitment has been recognized now that The Mount Sinai Hospital’s Neurology and Neurosurgery departments were ranked for the first time among the top 10 in the nation by U.S. News & World Report.

Joshua B. Bederson, MD

For decades, the departments have expanded clinical and research programs offering ground-breaking treatments for patients with a wide range of conditions, including cancer, brain tumors, and strokes as well as neurological disorders such as Parkinson’s disease, epilepsy, and multiple sclerosis, and psychiatric disorders such as major depression.

“Over the years, this process has involved recruiting the best and brightest neurosurgeons who align with my vision of highly specialized care, centers of excellence, and programs within each subspecialty that are as deep and as broad as an entire neurosurgery department,” says Joshua B. Bederson, MD, Leonard I. Malis, MD / Corinne and Joseph Graber Professor of Neurosurgery and System Chair, Department of Neurosurgery. “It’s also been meaningful to collaborate with the Department of Neurology to support their own recruits and create joint programs that provide comprehensive, well-rounded care to patients with neurological conditions.”

Added Barbara G. Vickrey, MD, MPH, System Chair, Department of Neurology, and Henry P. and Georgette Goldschmidt Professor of Neurology: “Our ranking is an acknowledgement of the Neurology Department’s leadership in clinical care on a national basis. We excel in treating the most challenging neurological patients and providing high-quality care to all of our New York City communities, including those that are under-resourced.”

In this Q&A, Dr. Bederson and Dr. Vickrey discuss how changes they have made over the years have helped patients.

What are some of the most significant changes the Department of Neurosurgery has made?

Over the past several years, our focus has been on building our divisions that deal with different disease states such as brain tumors, vascular problems and stroke, pediatric neurosurgery, movement disorders, and epilepsy. We recruited the nation’s best and brightest leaders in each one of these areas, building programs around their expertise into very strong, and sometimes very large divisions, many of which rival the average neurosurgery department in other parts of this country.

What are some national and global accomplishments?

Some of our national and global accomplishments focus on the creation of the division sub-specializations. In the cerebrovascular space, we recruited one of the world’s great leaders, Dr. J Mocco, to direct our Cerebrovascular Center, and he’s turned it into a very large service line with 10 full-time faculty. We are making groundbreaking changes to clinical treatment, including reducing the “time to needle” and treatment from the onset of stroke down to very low numbers, meaning very fast treatment times. We are achieving results that are the best in the world.

We’ve created centers of excellence around movement disorders, with one of the great deep brain stimulation programs and neurostimulation for intractable epilepsy. We have one of the largest pituitary tumor, skull base surgery, and malignant brain tumor programs in the country, with numerous NIH-funded research studies, and a large number of novel clinical trials in each of these areas. Our Division of Neurocritical Care is a large, world-class division with a unique Neuro Emergencies Management and Transfers (NEMAT) program transferring more than 1,000 patients with critical neurological illness every year.

How does the Department of Neurosurgery advance industry and academia?

Neurosurgery is inherently a technological field, and we rely very heavily on advanced digital and other technologies in the operating room. Through a significant partnership with industry, we have innovated in many creative ways, including in the use of augmented and virtual reality and the use of artificial intelligence that support our advanced digital platforms. We’ve created a new division called Sinai BioDesign, which is an incubator for innovative device creation. Here, surgeons work together with bioengineers to create new solutions for fixing problems that we face in the operating room and turn those solutions into products and companies.

How do these accomplishments result in better outcomes for neurosurgical patients?

All of our activities are aimed at improving patient outcomes. By creating centers of excellence, we can take advantage of our large health system by concentrating normally rare diseases into high volume centers, giving surgeons and other health care professionals the experience they need to become experts. They leverage the high volume to develop clinical protocols and research protocols that allow us to advance care in each disease state. Sinai BioDesign is creating new solutions and devices to help us treat conditions that require new solutions through advanced technologies, improving safety for patients.

Barbara G. Vickrey, MD, MPH

What changes has the Department of Neurology made?

The Neurology Department has grown dramatically in education, research, and clinical care in the last five years. Our department has had an approximately two-and-a-half-fold increase in NIH funding over five years. We have recruited more than 70 new faculty, who have been recruited both internally from our talented Mount Sinai graduates and from major academic institutions around the United States.

What are some specific areas of success?

We strive to improve outcomes in multiple sclerosis, Parkinson’s disease, stroke, epilepsy, headache, neuropathies, brain and spinal cord tumors, dementia, and other neurological disorders in children and adults, and we have subspecialty fellowship training programs in all these areas.  We have well-regarded centers, programs, and divisions that are dedicated to this mission, such as the Corinne Goldsmith Dickinson Center for Multiple Sclerosis, which is known for providing the best available multiple sclerosis care, including access to a wide range of clinical trials and a wellness program.

How does this make a difference for patients?

The Department provides patients with a unique blend of personalized and coordinated care, groundbreaking research, and technology. This integrated approach is instrumental in our pursuit of improving outcomes.

Can you give some examples?

Patients who come to our Comprehensive Stroke Center experience better outcomes on average than those of other New York City hospitals and other comprehensive stroke centers. Our Epilepsy Program provides a spectrum of treatments from the latest medications to vagal nerve stimulation and coordinates with Neurosurgery when surgical intervention is needed, with the goal of living seizure-free. Our patients in any subspecialty can count on physicians who have experience with unusual disorders as well as more common ones. In short, patients can expect to experience the benefits of a large, academic medical center along with personalized care. It’s the best of both worlds.

Learn more about Neurosurgery at Mount Sinai
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New Division of Data Driven and Digital Medicine Within the Department of Medicine

Updated on Nov 19, 2025 | Announcements, Artificial Intelligence

We are pleased to announce the establishment of a new Division of Data Driven and Digital Medicine within the Department of Medicine at the Icahn School of Medicine at Mount Sinai. Led by Girish N. Nadkarni, MD, the Division’s mission is to create a data science and digital health hub to catalyze translational research.

Recognizing that so much of what we do is driven by data, we are establishing this division as a critical step toward integrating data science and digital tools into clinical practice. Creating a hub within the Department of Medicine that promotes data science and digital health resources will augment and empower translational research and clinical care. Another priority for this new Division will be exposing medical students, residents, and fellows to the world of data science and digital health. The division will collaborate with many Icahn Mount Sinai entities, including the Mount Sinai Clinical Intelligence Center, the Hasso Plattner Institute for Digital Health at Mount Sinai, the Clinical Data Science team, The Charles Bronfman Institute for Personalized Medicine, the Scientific Computing and Data Science team, and others.

Dr. Nadkarni has demonstrated his passion for and skill with data-driven science, most recently as co-director of the Mount Sinai COVID Informatics Center. Along with Alexander Charney, MD, and a transdisciplinary group of collaborators, Dr. Nadkarni led data-driven efforts to understand and address COVID-19, which led to clinical trials that have had an impact on clinical care.

Dr. Nadkarni’s scientific interests beyond COVID-19 are reflected in his role as Principal Investigator on several projects funded by the National Institutes of Health and his authorship of more than 200 peer-reviewed publications. Additionally, he is a named inventor on multiple patents. In 2018, Dr. Nadkarni was a scientific cofounder of RenalytixAI, an artificial intelligence-enabled in vitro diagnostics company that collaborates with Mount Sinai in seeking to improve chronic kidney disease detection, management, and treatment.

By creating the Division of Data Driven and Digital Medicine, the Department of Medicine now has one of the first data science and digital health divisions of Medicine in the country, putting us at the forefront of an emerging field. We are extremely proud that we are breaking new ground by its establishment.

Please congratulate Dr. Nadkarni on his leadership role in this initiative.

Dennis S. Charney, MD, Anne and Joel Ehrenkranz Dean, Icahn School of Medicine at Mount Sinai, President for Academic Affairs, Mount Sinai Health System

David C. Thomas, MD, MHPE, Acting Chair, Department of Medicine, Vice Chair of Education, Department of Medicine, Mount Sinai Health System

Artificial Intelligence Tools May Detect Abnormalities that Could Otherwise Be Missed

Updated on Nov 19, 2025 | Artificial Intelligence, Featured, Research

Mount Sinai radiologists are comparing machine-read patient discharge summaries with original, human-read reports.

A patient’s electronic health record typically contains a trove of information that can be used to help predict and manage their future health needs. But much of that information is often composed of unstructured or fragmented data that first must be translated into language that physicians are able to understand.

A new partnership between the Mount Sinai Health System’s Department of Radiology and an Israel-based start-up, Maverick Medical AI, is exploring how to accomplish that task through the use of artificial intelligence. In a proof-of-concept study, Maverick’s deep learning and natural language processing (NLP) algorithms are being used to accurately identify co-morbidities in 1.5 million patient discharge summaries and radiology reports. If it is successful, Maverick’s program could open the door for its use in an array of medical, research, and business opportunities at Mount Sinai.

David Mendelson, MD

David Mendelson, MD, Vice Chair of Radiology Information Technology at the Icahn School of Medicine at Mount Sinai, is playing a key role in the research. He says one of Maverick’s strengths is its ability to report on secondary abnormalities in nearby organ systems that are sometimes only partially seen or could possibly be overlooked in radiological screenings.

“If someone is screened for lung cancer and the findings are negative, that’s great news for the patient,” says Dr. Mendelson. “But if natural language processing could identify secondary indications like coronary artery calcification or abnormal density of the liver, which might suggest non-alcoholic fatty liver disease, that information could prove very useful to physicians and patients. Physicians might be able to take preventive steps to improve outcomes for patients and ultimately lower health care costs downstream.”

Determining whether Maverick’s propriety algorithm can provide that important information is the responsibility of Pamela Argiriadi, MD, Assistant Professor of Diagnostic, Molecular and Interventional Radiology at Mount Sinai. Dr. Argiriadi and a team of residents are spot-checking secondary co-morbidities extracted by the algorithm from an ocean of radiology reports and discharge summaries to determine how they compare to the original, human-read reports.

“Radiology reports contain a wealth of information and we hope our study will shed light on how key-word phrases in those documents can be mined to provide input into the well-being of patients,” Dr. Argiriadi says. “A major goal of ours is to improve communication with primary care providers by reporting secondary findings to them, which can result in follow-up treatment and preventive medicine.” The software can recognize these findings within the report, extract them, and flag them for the provider.

Yossi Shahak, Co-founder and Chief Executive Officer of Maverick Medical AI, estimates that as much as 80 percent of a patient’s health information remains untapped due to its unstructured format. Translating that raw, fragmented data into medical coding language would provide physicians with actionable clinical insights.

“We are starting with radiology and hope to expand the vocabularies across many medical subspecialties, like cardiology and gastroenterology,” says Mr. Shahak. “That expansion of our data sets could provide Mount Sinai physicians with significant value when they mine it for often overlooked chronic conditions and risk factors. In addition, the conversion from unstructured data into medical coding will help Mount Sinai improve their financial capabilities.”

Read more Featured stories from Mount Sinai

Mount Sinai Researchers Streamline Patient Data to Find Patterns in COVID-19 Patients

Oct 29, 2020 | Artificial Intelligence, Featured, Research

Girish Nadkarni, MD

With the influx of patient data resulting from the SARS-CoV-2 pandemic, the Mount Sinai COVID Informatics Center is collaborating with London-based software company Clinithink to uncover key findings that can enable better treatment methods for COVID-19 patients.

Clinithink’s artificial intelligence platform, CLiX, processes large volumes of data from physician notes and documents within electronic health records, allowing providers to save time and effectively determine key information on patient conditions.

“We are currently using the platform to mine clinical documents in order to extract information to further our understanding of COVID-19 and its complexities, so we can determine the best course of action for individual patients,” said Girish Nadkarni, MD, Assistant Professor, Department of Medicine (Nephrology), Clinical Director of the Hasso Plattner Institute for Digital Health, and Co-Director of the Mount Sinai COVID Informatics Center.

Through the use of Clinithink’s platform “CLiXTM unlock,” the COVID Informatics Center is creating risk scores for COVID-19 patient symptoms, sifting through data that has been stripped of any personal information to find patterns that can ultimately lead to new discoveries in COVID-19 treatment.

“Clinithink is enabling us to identify and distinguish the symptoms in hospitalized COVID-19 patients during admission, in order to determine if and when new symptoms are appearing during their hospitalization,” Dr. Nadkarni said.

The Icahn School of Medicine at Mount Sinai was the first academic institution in the nation to partner with Clinithink in 2016, its original use to accelerate the prescreening process to identify eligible candidates for clinical trials.

“The collaboration between Clinithink and Mount Sinai represents how novel research can be translated into clinical practice,” Chris Tackaberry, CEO of Clinithink, said. “We are delighted to see Mount Sinai extend the use of our platform as they continue to make breakthrough discoveries in COVID-19.”

The collaboration was facilitated by Mount Sinai Innovation Partners (MSIP), the technology commercialization engine at Mount Sinai.

“Collaborating with Clinithink improves the way we understand and serve our patients,” said Erik Lium, PhD, President of MSIP and Executive Vice President and Chief Commercial Innovation Officer at the Mount Sinai Health System. “We look forward to seeing how Dr. Nadkarni’s team leverages Clinithink to extend our knowledge about COVID-19, and potentially improve treatment and patient outcomes.”

Read more stories about Research at Mount Sinai

SinaInnovations 2019: A Close-up Look at Artificial Intelligence

Nov 25, 2019 | Artificial Intelligence, Featured, Research

Keynote speaker Michael Snyder, PhD

What is the role of artificial intelligence (AI) in medicine, and how is it changing the practice of health care as we know it? That was the subject of the eighth annual SinaInnovations Conference, held Tuesday, October 15, and Wednesday, October 16, in Stern Auditorium. The event featured leading physicians and scientists from academia and industry who spoke about their work in deploying AI—the most powerful technology under development—to augment discovery and clinical use.

Experts shared their experiences in using AI in a variety of ways, from medical imaging, to predicting disease, to keeping people healthy, and highlighted the massive transformation taking place in health care and medicine, where software is driving innovation.

Michael Snyder, PhD, Chair of the Department of Genetics, and Director of the Center for Genomics and Personalized Medicine at Stanford University, a keynote speaker, discussed the role of AI in advancing personalized medicine. “I see a world where, with genome sequencing and continuous monitoring using wearable devices, we can better manage people’s health and hopefully do this at an individual level, and have personal machine-learning algorithms that follow people and their health state,” Dr. Snyder said. “We’re very capable of measuring more things, and here’s an area where AI can make a big impact.”

Melissa A. Haendel, PhD, Director of Translational Data Science at Oregon State University, spoke about her work in leading the federally funded Monarch Initiative, which is building sophisticated algorithms that integrate a multitude of data about rare diseases in order to improve research and clinical care. “No one group is actually annotating a disease model that has all the same attributes,” Dr. Haendel said. “We can’t even count the number of rare diseases.” Her team’s goal, she said, is to pull all of the data together and use it to build models that help physicians make earlier diagnoses, identify biomarkers of disease, and find better treatments.

Conference participants Heather J. Lynch, PhD, Associate Professor of Ecology and Evolution, Stony Brook University, left, and Georgia D. Tourassi, PhD, Director, Health Data Sciences Institute, Oak Ridge National Laboratory.

David Sontag, PhD, Associate Professor of Electrical Engineering and Computer Science at Massachusetts Institute of Technology, discussed how AI can be used to redesign electronic medical records so they can yield more reliable information on the patient’s risk for various diseases. In one case, he said, his team developed a machine-learning algorithm to help an infectious disease clinician at Massachusetts General Hospital and Brigham and Women’s Hospital reduce the number of unnecessary prescriptions for antibiotics.

AI is already playing a role in augmenting radiology. Keith J. Dreyer, DO, PhD, Vice Chairman, Radiology, at Massachusetts General Hospital and Chief Science Officer of the American College of Radiology, told the audience that “AI has huge value” and will be increasingly useful over time as the field matures.

In his keynote address, Pieter Abbeel, PhD, an entrepreneur and Professor of Electrical Engineering and Computer Science at the University of California, Berkeley, showed how deep machine learning takes place through constant repetition. In one example, he illustrated how a robot learns to run. After 2,000 iterations, it will become proficient. By comparison, a healthy human child would learn to run proficiently after roughly two weeks of practice. In many cases, he said, machines have achieved human-level error rates.

Among the many algorithms Stanford University is working on is one that recognizes the photo of a radiological image taken with a mobile phone, according to Curtis Langlotz, MD, PhD, Director of Stanford’s Center for Artificial Intelligence in Medicine and Imaging. This technology would allow general practitioners and other health care professionals in remote areas to use their mobile phones to access an algorithm that would assist them in making medical decisions when a radiologist is not available. For example, they would be able to determine whether a patient with, say, tuberculosis, should be discharged from the hospital.

Speakers and attendees at the conference agreed that AI is both promising and challenging. Suresh Venkatasubramanian, PhD, Professor of Computing at the University of Utah, cautioned that inherent bias in the data will create bias in the algorithms. “Models are fragile,” he said. “The Achilles heel is that the more sophisticated a system gets, especially with deep learning, the more sensitive it gets to small perturbations, and this could wreak havoc on the system.”

Greg Zaharchuk, MD, PhD, Professor of Radiology (Neuroimaging and Neurointervention) at Stanford University, concluded his talk with a nod to the future. “I think we’re only scratching the surface. This is a moment of extreme creativity, and it’s a very exciting time to be in the field.” Rather than replacing radiologists and other medical specialists, he added, AI “is really going to extend our abilities as physicians.”

New Gift Supports Young Entrepreneurs at Mount Sinai

This year, for the first time, a nonprofit biotech accelerator company founded by five former postdocs at the Icahn School of Medicine at Mount Sinai presented the school with a five-year, $50,000 gift to support young entrepreneurs in the New York City area whose science is being used to create therapies, devices, and diagnostics that support human health. The gift from The Keystone for Incubating Innovation in Life Sciences (KiiLN) went to Raymond A. Alvarez, PhD, Assistant Professor of Medicine (Infectious Diseases) at the Icahn School of Medicine at Mount Sinai, who is working on a platform that identifies and studies the antibodies of individuals who are immune to hantaviruses, which are spread by rodents and have a 38 percent mortality rate. Currently, there are no vaccines or treatments for hantaviruses.

 

2019 Mount Sinai Health Hackathon Winners

Nov 25, 2019 | Artificial Intelligence, Featured, Research

The three team finalists were: George:  Katie Depue, David Koellhofer, and Brendan Reilly.  Deliberate: Marc Aafjes, Michael Balangue, Do Hyung Kwon, Hansaim Lim, and Paulo Serodio. Deep Brain Precision: John Di Capua, Taylor Miller, Ashley So, and Danielle Soldin.

One hundred eighty medical and graduate students, and others, formed 19 teams to participate in the fourth annual Mount Sinai Health Hackathon in October. The 48-hour competition, held over the weekend leading up to the SinaInnovations Conference, challenged the participants to create novel health care solutions that would expand the limits of human performance.

Three teams each received checks totaling $2,500 and will have the opportunity to pitch their ideas again in 2020 at Mount Sinai’s Innovation Showcase before a group of entrepreneurs and venture capitalists. They will be joined by a fourth wild-card team chosen from the non-finalists.

Scott L. Friedman, MD, Dean for Therapeutic Discovery, and Chief of the Division of Liver Diseases at the Icahn School of Medicine at Mount Sinai, told the participants, “We started this event four years ago as part of a larger effort to spur innovation. This is really the embodiment of our values about teamwork and doing great things.”

The three team finalists were:

Deliberate: Improving the quality of care in psychotherapy through confidential recording and analysis. Team members: Marc Aafjes, Michael Balangue, Do Hyung Kwon, Hansaim Lim, and Paulo Serodio.

George: An artificial intelligence application that allows dialysis providers to optimize scheduling and improve a clinic’s efficiency. Team members: Katie Depue, David Koellhofer, and Brendan Reilly.

 Deep Brain Precision: An app that would allow physicians to monitor a patient’s progress after receiving deep brain stimulation for Parkinson’s disease and other motor disorders. Team members: John Di Capua, Taylor Miller, Ashley So, and Danielle Soldin.

Sponsors and partners: Accenture; Altice Business; Cisco; Farmer’s Fridge; Kitware; PepsiCo; Persistent Systems; the National Center for Advancing Translational Sciences, National Institutes of Health; and the Christopher & Dana Reeve Foundation.

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