Powered by Artificial Intelligence
ABOUT US
A model integration-first AI platform,
that will enable automation, recognize hidden patterns and capture key insights.
Jiva.ai empowers organizations with the tools and computation capacity to create Machine Learning models so that they can make the most out of their data.
Predict
outcomes and recognize hidden patterns
Solve
healthcare problems
& improve efficiencies and human health outcomes.
& improve efficiencies and human health outcomes.
Enhance
existing capabilities by arming them with AI-driven custom software
FOCUS
Machine Learning
Healthcare systems must operate under the strain of ever-increasing patient demand whilst maintaining an acceptable level of care.
AI and machine learning can help reduce that burden by saving both time and money in diagnosis, automation and proactive prediction.
Jiva.ai can provide quantifiable value to the healthcare sector
Smart diagnosis
Clinical trial backed solutions to enhance and aid the current diagnostic pathway
Proactive detection
Integration of Jiva solutions into hospital systems, such as PACS, for frictionless and automated processes
Live Monitoring
Realtime speed of execution, triggering fast alerting for medical staff
Custom solutions
Have a specific use case?
Let’s talk. Jiva.ai is extremely versatile and can be shaped to specific requirements
Let’s talk. Jiva.ai is extremely versatile and can be shaped to specific requirements
We currently work with the following core healthcare and life sciences segments
Health Services Providers
Pharma Life Sciences
Consumer Health
Medical Insurance
SOLUTION
Jiva.ai
Jiva.ai is deployed via a simple 3 step process
1
Data aggregation
to extract relevant
information in real-time for
our algos to analyse
information in real-time for
our algos to analyse
2
Recognition
of patterns and
anti-patterns
anti-patterns
3
Adaptive learning
Jiva.ai gets smarter over time
Here are a few use-cases that Jiva.ai is currently deployed to solve or in consultation
- USE CASE 1
- USE CASE 2
- USE CASE 3
- USE CASE 4
- USE CASE 5
MRI Imaging Analytics for Prostate Cancer
Prostate cancer is set to become the most common cancer in men with approximately 50,000 new cases every year. Subjectivity in diagnosis is a known issue with sensitivity recorded as low as 57%. A high time and economic cost of post-biopsy complications means that radiologists are under increasing pressure to improve efficiency.
Jiva.ai is set to become the first AI-based solution trained on a unique set of labelled T3 MRI scans to identify tumours that would otherwise be missed. The trained kernel is due to go to clinical trial in late 2019/early 2020.
Live Analytics
A single patient in ICU in a single hospital is replete with data. Diagnostic machines, tests, results, notes – all contribute to the live data stream. These silos can be integrated to deliver super fast diagnostic and monitoring care.
Bone Fracture Diagnosis
Doctors in A&E are overworked, tired and pressured – they need every bit of help they can get. Moreover junior staff can have an error rate of up to 30% in identifying fractures from scans. Jiva.ai has teamed up with RGU to deliver an automated tool to diagnose fractures quickly and efficiently.
Preventative Medicine
Jiva.ai is a model integration technology for complex systems; and it doesn’t get much more complex than molecular medicine. Using our machine learning platform we are putting together a suite of genomics and proteomics tools that will encourage drug discovery and development.
Falls Pathway
A model integration-first AI platform,<br /> that will enable automation, recognize hidden patterns and capture key insights.Jiva.ai empowers organizations with the tools and computation capacity to create Machine Learning models so that they can make the most out of their data.
TECHNOLOGY
Under the Hood
The algorithm that powers Jiva.ai is a class of deep learning, similar to TensorFlow, but with a different flow of execution. The main difference is that Jiva.ai incorporates real-world semantics into the model. This allows the ability to not only modify the model iteratively, but also integrate different models together.
For example, you may want to integrate kernels (predictors) between the following markers:
(a) Genetic markers for diabetes
(b) Genetic markers for heart disease
(c) Socio-demographic factors
age, income, house prices, environmental factors, etc
These models can be learned separately, and integrated later, this would highlight any co-factors or anomalies worth investigating. This also allows us to have an AI algorithm more suitable for real world problems. The idea is to improve your machine learning capability over time. As disparate kernels get added Jiva.ai will evolve its general artificial intelligence.
WHO IS JIVA?
Our team with Big Ideas
Dr Chetan Kaher
Business & Growth
Chetan has a doctorate in dentistry and a BSc in Immunology & Oncology with publications in developing anti-cancer proteins. He is currently on the NHS Clinical Entrepreneurship Scheme, to implement Jiva.ai into healthcare systems.
Dr Manish Patel
Technical Lead
Manish has a doctorate in mathematical modelling with an emphasis on dealing with large, complex datasets. He is the technical architect of Jiva.ai, a new machine learning algorithm that will form the basis of a new breed of AIs.
Sarah D’Souza
CIO & Operations
Sarah is an experienced management and banking professional with a background in law. As well as being a successful entrepreneur, Sarah joins the team taking control of project management, operations and all things legal & data security.
Dr Andrew J. Thompson
Funding Strategy
Andy heads funding strategy and is a professional grant writer. He has extensive experience developing business, R&D and fundraising strategy, and preparing and implementing winning business cases.
