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Have you ever ever observed a spot in your pores and skin and puzzled if it might be one thing severe? Puzzled in case your cough indicated COVID or simply the run of the mill flu? Want you may test your blood strain along with your smartphone? Enter Helfie.ai, an rising healthcare startup within the healthcare sector who’re harnessing multli-modal AI algorithms designed to assist sufferers shortly and precisely test for a spread of healthcare circumstances. With groups in Australia and Denmark, Helfie.ai goals to make healthcare extra accessible and inexpensive by enabling sufferers to research their well being circumstances from the consolation of their houses, utilizing solely their smartphone.
Helfie.ai is constructing an answer that caters to healthcare suppliers who can arm their sufferers with an utility to extra shortly and precisely entry the care they want Helfie.ai’s AI mannequin analyzes footage, movies, sound recordings by way of a sufferers’ cellular system to test for indicators of potential well being circumstances. A few of the diagnoses they assist are respiratory well being, vitals, and pores and skin most cancers. The product helps real-time physician help to substantiate the prognosis and prescribe the suitable therapy.
All assessments offered by Helfie’s AI are tentative indications of a potential situation, not an precise prognosis. These assessments are not at all an alternative to private session, screening, prognosis or therapy by a registered well being practitioner. Helfie apps shouldn’t be used to make selections in conditions which are life-threatening.
Helfie.ai is a part of the Microsoft for Startups Pegasus program, which supplies entry to Azure credit, Go-to-Market (GTM), technical assist, and distinctive advantages corresponding to entry to Azure AI infrastructure on a devoted GPU cluster.
Helfie.ai is leveraging a devoted NDm A100 v4-series cluster in Azure ML to coach and finetune the AI mannequin that energy their resolution. Due to the necessity for scientific grade predictions a few affected person’s well being situation, their flagship product, Very important’s AI, analyzes photos, video and sound recordings to guage well being circumstances and make distant assessments.
By utilizing the devoted GPU cluster of A100s, Helfie.ai’s CTO Nikhil Sehgal, reviews that through the use of the devoted GPU cluster of A100s, they’ve diminished their mannequin coaching time from two weeks to simply two hours.
“The drastic discount in mannequin coaching time is important for a startup like us, it permits us to construct quicker and get our product into the fingers of customers,” Sehgal tells Microsoft for Startups.
The GPU cluster additionally permits them to scale up their fashions as they develop their person base and information sources, guaranteeing that their merchandise can deal with the rising demand and complexity. Working workloads on Azure additionally helps them seamlessly adjust to compliance insurance policies just like the Well being Insurance coverage Portability and Accountability Act (HIPAA) and Basic Information Safety Regulation (GDPR).
Helfie.ai has developed specialised AI fashions, generally known as “AI Specialists,” fine-tuned for particular medical domains. For example, the “Cardiology AI” is an LLM (Massive Language Mannequin) with complete data in cardiology, enabling customers to obtain expert-level responses just like these from an expert heart specialist. Helfie.ai accomplishes this by accumulating respected literature and documentation from the net to fine-tune each open-source LLMs and flagship GPT-series fashions.
To create and monitor these fashions, Helfie.ai makes use of Azure ML Studio for machine studying experiments, hyperparameter optimization, and efficiency reporting. The corporate depends on Azure Kubernetes Service (AKS) for intensive computational duties, Azure OpenAI for multimodal LLM capabilities, and Azure AutoML for optimizing hyperparameters. They ran each classification and pc imaginative and prescient mannequin experiments on Azure ML. Via these experiments, Helfie.ai was capable of optimize hyperparameters together with perfect n_estimators and max_depth.
Helfie’s assessments typically contain visible or audio inputs, demanding outstanding computational bandwidth to coach their workloads. A major problem was re-training the pores and skin most cancers prediction mannequin utilizing smartphone photos of lesions. To handle this, Helfie.ai established its total coaching pipeline on Azure’s devoted GPU cluster, bettering throughput per epoch as new information from tutorial establishments necessitated frequent re-training.
To handle information privateness, Helfie implements sturdy AI content material security insurance policies to make sure person interactions with specialist LLMs are secure and stay confidential. This consists of Azure AI Content material Security Dashboard, a real-time dashboard that flags responses with potential dangers, serving to to forestall any dangerous person actions.
Helfie.ai’s merchandise—Vitals AI, Respiratory AI, STI AI, and Skin AI—are actually accessible on Azure Market.
Devoted GPU clusters can be found for startups on Microsoft for Startups who’re backed by one among Microsoft’s strategic VC companions: Microsoft expands free Azure AI infrastructure access to startups | Microsoft for Startups Blog, together with Startups who’re energetic within the Pegasus Program.
