Edward Belgeonne, Founder & CEO, Bantham Technologies
The RADAR platform is data agnostic, meaning it can ingest any data structure, be it numerical, textual, or picture-based, allowing for a wide range of applications ranging from image analysis to treatment prediction.
FREMONT, CA: Bantham Technologies, a digital data capture solutions provider, recently launched Bantham RADAR, an AI Machine Learning platform developed in collaboration with AGXIO, AI, data science, and machine learning company to assist healthcare professionals in gaining better insights and recognizing data patterns that improve clinical, operational, and financial decision-making, improving patient outcomes while reducing clinical staff workload. It comes as the NHS recently revealed that waiting lists have reached a 14-year high of 4.7 million people. RADAR operates by deploying autonomous data science robots that perform at a high level of precision.
“Bantham RADAR focuses on problems that are beyond human scale in dimension or complexity,” says Edward Belgeonne, CEO & founder, Bantham Technologies. “Typically, a problem may have tens or even hundreds of millions of data points which must be analysed during the data modelling phase. In addition, there are tens of thousands of different machine learning models that may need to be considered before selecting the optimum model. Bantham RADAR makes this so much easier than before and brings AI into the realm of the everyday domain user, not just the statistical expert.”
These robots analyze data to create predictive models, which are then analyzed to find trends, parameters, and issues in all aspects of healthcare. RADAR has been designed primarily for clinicians and key decision-makers to use in their daily operations. Clinicians may now make full use of all of their data and make better-informed decisions without the need for specialized skills or costly retraining by automating the function of the data scientist.
RADAR was developed in collaboration with Agxio Limited, an award-winning AI and Data Science firm. Agxio, supported by the Development Bank of Wales, is a principal specialist in the biotech, life sciences, and agricultural science industries. The CEO of Agxio, Dr Stephen Christie, stated that “Automated machine learning solutions delivered with a range of explainable metrics will provide a quantum leap for the healthcare industry. We are delighted to be collaborating with Bantham Technologies to provide the underlying engine, Apollo, on this ground-breaking Medically explainable AI platform (MXAI).”
“MXAI has the potential to transform how AI is used in healthcare; delivering a range of explainable metrics which is both comprehensible to the practitioner and meets the GDPR requirements in terms of transparency of decision making and explainability. Crucially MXAI will enable practitioners and regulators alike to extend the application of image analytics to a far broader practitioner space. Applications such as Bantham RADAR must not simply be confined to a small number of specialist super-users, they must be relevant, comprehensible and practical to a far wider user group than is currently the case, if they are to have real impact and effect positive change,” adds Belgeonne.
The RADAR platform is data agnostic, meaning it can ingest any data structure, be it numerical, textual, or picture-based, allowing for a wide range of applications ranging from image analysis to treatment prediction. RADAR produces outcomes in hours, often minutes, by automating procedures that would usually take weeks or months to complete. RADAR digested 2,500 brain scans in a recent test and delivered its conclusions (identifying distinct types of brain tumors) in three minutes, with an initial efficacy rate of 84 percent. After only two hours of instruction, this was accomplished. Following further refinement of the model, efficacy rates reached as high as 99.83 percent in some circumstances.
RADAR expects to deploy three modules in the coming months: Community Data, Acute Data, and Digital Pathology. The Community Module extracts clinical trends from District Nurse and Outpatient activities, the Acute Module extracts clinical trends from patient data sets for on-site clinicians, and RADAR Pathology ingests diagnostic images such as X-rays, MRIs, and CT scans to improve the speed and accuracy of diagnosis in a variety of settings.
“RADAR helps healthcare professionals see what has happened, why has it happened and what is likely to happen in the future as a result. It is a truly intelligent, unbiased, neural engine that is highly configurable, infinitely scalable and capable of having a huge and positive impact on patient outcomes,” said Belgeonne.
The UK Parliamentary Office of Science and Technology released its AI and Healthcare Research report earlier this year, emphasizing the importance of AI in the healthcare business. Belgeonne argues that if the NHS is ever to return to pre-pandemic normalcy, it will need to embrace technology like never before, with roughly 5 million procedures canceled since the outbreak of Covid 19.
Belgeonne concludes, “As the pressure on the NHS begins to subside to more manageable levels, it is becoming increasingly clear that COVID has created an enormous backlog within mainstream healthcare activities; one which simply cannot be managed downwards without the wide-scale adoption of technology and new ways of doing things. We sincerely hope that RADAR will play a part in that.”