Welcome to MetastaticAI

At Metastatic AI, we leverage the powers of deep learning to solve some of the world's most puzzling problems in medicine, healthcare, and life science research.
Selected among the top five healthcare startups in the country to pitch at MSD Healthcare Innovation & Technology Conference
We reduce patient suffering by decreasing the time to diagnosis, avoiding unnecessary medical procedures, and reducing treatment related expenses.


At Metastatic AI, we have developed a proprietary deep learning library that allows us to generate high-performance deep learning models specifically designed to diagnose some of the world's most challenging diseases. By harnessing the power of neural networks, our algorithms can decipher interactions too complex for the human brain to comprehend. This cloud based AI engine is currently being used to power our AI-assisted diagnostics platform as well as revolutionize the life science and biomedical research fields.


The main focus of Metastatic AI is to provide AI-assisted diagnosis with levels of accuracy unobtainable by modern day physicians. While the human brain has a remarkable ability to process complex visual information, our ability to process numerical data pales in comparison to our computer counterparts. To aid physicians in interpreting complex medical data, Metastatic AI's deep learning engine was trained on extensive amounts of real patient data to achieve diagnostic accuracies over 99%. By removing potential human error from diagnoses, we aim to eliminate misdiagnosis, increase patient survival, and decrease unnecessary medical spending.


Our AI engine isn't just for clinical diagnoses. Metastatic AI's models are currently being utilized to modernize scientific innovation. Utilizing a wide variety of data, such as genomic, proteomic, and molecular binding data, Metastatic AI is accelerating the process of scientific discovery. Our models are being utilized by scientists to assist with drug discovery, predict protein-protein interactions, and isolating genetic risk factors to advance personalized medicine. By harnessing the processing power of machine learning, there is no limit to our level of discovery. Have a problem our AI engine can solve? Contact us today.


Metastatic AI's breast cancer diagnosis engine is a cloud-based deep learning engine capable of detecting abnormal patterns in digitized fine needle aspirate images of the breast. Metastatic AI's algorithms were trained on a combination of a well-known breast cancer dataset and clinical data obtained from our collaborators. This combination of datasets has allowed Metastatic AI's breast cancer diagnosis engine to achieve a diagnosis accuracy of over 99% in nanoseconds of processing time. Interested in becoming a clinical partner? Contact us today.


Anabetsy Rivero, CEO

Ms. Anabetsy Rivero is a computer and data scientist with a background in a biochemistry and molecular biology. She has worked at several research laboratories at Harvard Medical School and University of Miami Miller School of Medicine Sylvester Comprehensive Cancer Center. Ms. Rivero started her research career at Harvard Medical School where she worked under Dr. Robert Sackstein. In the Sackstein lab, Ms. Rivero studied the role of adhesion molecules in cancer metastasis, specifically E-selectin ligands, as well as the expression of all variants of HCELL present in pancreatic, colon, liver, and breast cancer. She was selected to join the prestigious Harvard Summer Undergraduate Research Program in Immunology where she was trained by some of the world's leading immunologists including Shiv Pillai, Shannon Turley, and Vijay Kuchroo. In 2015, while working in oncogenomics and protein biochemistry at the laboratory of Dr. Ramin Shiekhattar, she realized that data analysis would play a much greater role in genomics. It was this realization that compelled her to join the graduate computer science program at Nova Southeastern University where she met Dr. Rajput and began developing Metastatic AI. During her masters, Ms. Rivero specialized in data science and artificial intelligence. Her expertise in AI covers areas such as data mining, supervised learning (including shallow and deep neural networks), unsupervised learning, natural language processing, information retrieval, recommender systems, and more. She has extensive experience managing scientific and software design and development teams in Miami and offshore. She oversees the data modeling, design and development of data science, business analytics, machine learning, and healthcare (HIPAA compliant) applications at Eepos IT Services.

Saeed Rajput, CTO

Dr. Saeed Rajput obtained his Ph.D. from Viterbi School of Engineering's Communication Sciences Institute of the University of Southern California in 1992 under the supervision of Dr. Lloyd Welch. During his time at Philips Research Laboratory, Dr. Rajput was the first to implement the Viterbi Algorithm on a signal processor. Since then, he has been an innovator with three patents and numerous publications. His specialties include network security, cloud computing, machine learning, and natural language processing. He has over a decade of diverse, creative, and visionary development experience in the fields of data, network and application security. Dr. Rajput has held senior-level positions as security director at eTrango, security/software architect at Milgo solutions (Racal Datacom), and vice president of engineering at Think-Sync, Inc. and Cerebit. In his academic career, Dr. Rajput has held the position of adjunct professor at University of Miami as well as assistant director at Nova Southeastern University, where he managed Computer Science, Information Systems, Engineering, Information Technology, and Mathematics programs. Currently, Dr. Rajput lectures on computer science at Florida Atlantic University and is a senior member of IEEE.

James Termini, CSO

Dr. James Termini is a microbiologist and immunologist with expertise in virology, cancer immunotherapy, personalized vaccine development, and genomics. He obtained his PhD from the University of Miami Miller School of Medicine. A large part of his research has been dedicated to the study of viral genomics and their relationship to viral infectivity as well as potential avenues for personalized vaccination. He has worked on the development of a novel dendritic cell immunotherapy for the treatment of cancer and HIV, the importance of O-glycosylation in HIV infectivity, and the use of adeno-associated virus for a protective vaccine against HIV. Dr. Termini's current funding includes grants from the State of Florida and the Centers for AIDS Research for the development of novel HIV vaccines and is the author of numerous scientific publications. He is the recipient of the 2017 CFAR award for research excellence and the recipient of the Procter and Gamble Research Award. In addition, he is the co-founder and managing partner at Eepos IT Services, where he oversees 40 software developers and designers. His vast experience managing software teams ranges from biomedical software, mobile banking and payment, and HIPAA compliant healthcare applications.


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