Nature Scientific Reports publishes novel decentralized federated AI learning algorithm that connects globally distributed data silos containing private and poor-quality data.

Nature Scientific Reports journal has published results of a new decentralized federated AI learning algorithm that can train AI on data that is distributed globally, without having to move private data to a central location. The breakthrough algorithm was able to achieve greater AI accuracy than traditional centralized AI training in real-world scenarios where data is poor-quality and contains errors, particularly when private data cannot be manually verified.

The algorithm, developed by AI company Presagen, presents a practical solution for connecting data silos and training AI in industries where data are sensitive and cannot be shared (moved), such as healthcare, defense, and finance. Research interest in distributed AI learning algorithms, called federated learning, has increased in recent years. However, many implementations have struggled with scalability, and typically require data to be transferred to a central location, potentially breaching data privacy.

Presagen’s Decentralised AI Training Algorithm (DAITA) approach ensures data privacy, is robust and is scalable as well as cost-effective for large real-world problems. Rather than moving data to the AI in a central location, the algorithm moves the AI to the location of the data, which can be distributed globally. Only the general abstract learnings from the AI trained on the data sources are shared, and never the individual datasets themselves.

Presagen Chief Scientist Dr Jonathan Hall explained “Using DAITA, we can optimise how the AI travels around the world – minimizing the cost of transfer, whilst simultaneously maximizing the performance of the final AI, all without looking at sensitive data.”

In collaboration with the Ovation Fertility network of IVF laboratories in the USA, the algorithm was applied to a healthcare problem of assessing the viability of embryos to assist embryologists in identifying embryos that are likely to lead to a pregnancy for IVF patients.

Ovation Fertility’s VP of Scientific Advancement, Dr Matthew (Tex) VerMilyea said “Embryo viability data has inherent errors. Patient embryos that are viable do not always lead to a pregnancy due to other factors related to the patient. Many problems in healthcare have poor-quality data, due to uncertainty or subjectivity.”

Presagen CEO Dr Michelle Perugini said “To train AI in healthcare that is unbiased and commercially scalable, you need to train AI on globally diverse data from clinics around the world, that represent different clinical settings and patient demographics. However, the challenge is that data privacy laws prevent sharing and centralizing medical data to train AI. Our decentralized AI learning algorithm addresses data privacy, data quality, and data diversity issues of connecting global data silos to AI for the benefit of patients around the world.”

Presagen has two commercial AI healthcare products in market globally, under its Life Whisperer brand for the fertility sector. Life Whisperer assess embryos for their viability and genetic integrity. Life Whisperer is currently being distributed globally by FUJIFILM Irvine Scientific.

Paper Title

A novel decentralized federated learning approach to train on globally distributed, poor quality, and protected private medical data

https://www.nature.com/articles/s41598-022-12833-x

Authors

T.V. Nguyen, M. A. Dakka, S. M. Diakiw, M. D. VerMilyea, M. Perugini, J. M. M. Hall, and D. Perugini

Paper Abstract

Training on multiple diverse data sources is critical to ensure unbiased and generalizable AI. In healthcare, data privacy laws prohibit data from being moved outside the country of origin, preventing global medical datasets being centralized for AI training. Data-centric, cross-silo federated learning represents a pathway forward for training on distributed medical datasets. Existing approaches typically require updates to a training model to be transferred to a central server, potentially breaching data privacy laws unless the updates are sufficiently disguised or abstracted to prevent reconstruction of the dataset.

Here we present a completely decentralized federated learning approach, using knowledge distillation, ensuring data privacy and protection. Each node operates independently without needing to access external data.  AI accuracy using this approach is found to be comparable to centralized training, and when nodes comprise poor-quality data, which is common in healthcare, AI accuracy can exceed the performance of traditional centralized training.

About Presagen

Presagen is an AI healthcare company that is changing the way clinics, patients, and medical data from around the world are connected through AI. Its platform, The Social Network for Healthcare, connects clinics and patients globally, and enables collaboration and data sharing to create scalable AI healthcare products that are affordable and accessible for all. The decentralized network democratizes the creation of AI products, promotes collaboration through incentives, and protects data privacy and ownership. With a focus on improving Women’s Health outcomes globally, Presagen’s first product, Life Whisperer, is being used by IVF clinics globally to improve pregnancy outcomes for couples struggling with fertility. With a vision of creating the largest network of clinics, patients, and medical data from around the world, Presagen is driving the future of AI Enhanced Healthcare.

About Ovation Fertility

Ovation® Fertility is a national network of reproductive endocrinologists and scientific thought leaders focused on reducing the cost of having a family through more efficient and effective fertility care. Ovation’s IVF and genetics laboratories, along with affiliated physician practices, work collaboratively to raise the bar for IVF treatment, with state-of-the-art, evidence-based fertility services that give hopeful parents the best chance for a successful pregnancy. Physicians partner with Ovation to offer their patients advanced preconception carrier screening; preimplantation genetic testing; donor egg and surrogacy services; and secure storage for their frozen eggs, embryos and sperm. Ovation also helps IVF labs across America improve their quality and performance with expert off-site lab direction and consultation. Learn more about Ovation’s vision of a world without infertility at www.OvationFertility.com.