School of Medicine
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Maxwell Greene, MD
Clinical Assistant Professor, Neurology & Neurological Sciences
BioDr. Greene is a board-certified, fellowship-trained neurologist. He is also a Clinical Assistant Professor of Neurology at Stanford University School of Medicine.
Dr. Greene provides clinical care for adult patients with disorders of the muscles and peripheral nerves that cause weakness and numbness. He specializes in diagnosing and treating neuromuscular diseases that include amyotrophic lateral sclerosis (ALS), all types of muscular dystrophy, chronic inflammatory demyelinating polyneuropathy (CIDP), myasthenia gravis, and Charcot-Marie-Tooth (CMT). For CIDP and CMT, Stanford is one of the few centers of excellence in the country.
A significant part of Dr. Greene’s practice involves investigational work, where he seeks to determine the cause of a patient’s symptoms. In addition to performing the full range of diagnostic tests including interpreting biopsy procedures, he has special qualifications in electrodiagnosis and the use of electromyography and nerve conduction studies.
Treatments offered by Dr. Greene cover the complete spectrum of options, with an emphasis on immune therapies for certain conditions. For CIDP and myasthenia gravis, he administers immune globulin, steroids, plasmapheresis, and rituximab. To help manage symptoms of CMT and support areas of the body weakened by this disease, he can recommend physical therapy, occupational therapy, and foot, ankle, and knee orthotics.
For the treatment of ALS and muscular dystrophy, Dr. Greene leads a multidisciplinary team offering physical and occupational therapy, pulmonary expertise, speech and swallow expertise, nutrition counseling, social services, and specialized nursing, and works together with genetic counseling. All team members collaborate closely to ensure patients receive the care and comfort needed to meet their emotional as well as physical needs.
As part of his commitment to advancing patients’ treatment options, Dr. Greene conducts clinical research. Among his current interests are
innovative new therapies for ALS and other nerve and muscular disorders. This is an exciting time in the field of neuromuscular medicine, with real potential for treatment breakthroughs for the first time in decades. Exploring these new directions enables Dr. Greene to offer Stanford patients access to options that may not be available anywhere else.
To highlight new advances for his peers, Dr. Greene has made national and regional presentations at conferences including the American Academy of Neurology meeting. Topics include the results of a study supported in part by the National Institutes of Health: paraneoplastic antibodies as markers of Hodgkin’s disease. JAMA Neurology published Dr. Greene’s article on this research.
Dr. Greene’s achievements have earned recognition from the American Academy of Neurology and other organizations. He is also the recipient of a travel award from the American Neurological Association and a grant from the NIH National Institute of Neurological Disorders and Stroke.
A member of the American Academy of Neurology, Dr. Greene is also an active member of the Western ALS Consortium and Northeastern ALS Consortium.
Michael Greicius, MD, MPH
Iqbal Farrukh and Asad Jamal Professor and Professor, by courtesy, of Psychiatry and Behavioral Sciences (Administrative and Academic Special Programs)
Current Research and Scholarly InterestsAs the Medical Director of the Stanford Center for Memory Disorders and Principal Investigator of the Stanford Extreme Phenotypes in Alzheimer's Disease (StEP AD) Cohort, Dr. Greicius' research focuses on elucidating the neurobiologic underpinnings of AD. His lab combines cutting edge brain imaging, "deep" phenotyping, and whole-genome sequencing of human subjects to identify novel pathways involved in AD pathogenesis. The goal of his work is to develop effective treatment for AD patients.
Postdoctoral Scholar, Neurology and Neurological Sciences
BioI am interested in exploring machine learning and deep learning methods for biomedical applications and medical imaging. Limited availability of labeled datasets to train machine learning models and large-scale variability in the datasets are some of the common challenges that I am interested in solving for the successful use of AI in this domain. Currently, I am exploring machine learning methods for genomics, where I am particularly focused on improving prediction for disease risk for Alzheimer’s disease for minority populations.