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Have you ever ever observed a spot in your pores and skin and questioned if it may very well be one thing severe? Questioned in case your cough indicated COVID or simply the run of the mill flu? Want you would verify 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 verify for a variety 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 means of a sufferers’ cellular machine to verify for indicators of potential well being circumstances. A few of the diagnoses they help 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 remedy.
All assessments supplied by Helfie’s AI are tentative indications of a doable situation, not an precise prognosis. These assessments are certainly not an alternative to private session, screening, prognosis or remedy by a registered well being practitioner. Helfie apps shouldn’t be used to make choices in conditions which might be life-threatening.
Helfie.ai is a part of the Microsoft for Startups Pegasus program, which offers entry to Azure credit, Go-to-Market (GTM), technical help, and distinctive advantages equivalent 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 medical grade predictions a few affected person’s well being situation, their flagship product, Very important’s AI, analyzes pictures, video and sound recordings to judge well being circumstances and make distant assessments.
Through the use of 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 only two hours.
“The drastic discount in mannequin coaching time is crucial for a startup like us, it permits us to construct quicker and get our product into the palms of customers,” Sehgal tells Microsoft for Startups.
The GPU cluster additionally permits them to scale up their fashions as they develop their consumer base and knowledge sources, guaranteeing that their merchandise can deal with the rising demand and complexity. Operating 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 Common Knowledge 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 amassing respected literature and documentation from the online 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 laptop imaginative and prescient mannequin experiments on Azure ML. By way of these experiments, Helfie.ai was in a position to optimize hyperparameters together with ideally suited n_estimators and max_depth.
Helfie’s assessments usually contain visible or audio inputs, demanding exceptional computational bandwidth to coach their workloads. A big problem was re-training the pores and skin most cancers prediction mannequin utilizing smartphone pictures of lesions. To deal with this, Helfie.ai established its complete coaching pipeline on Azure’s devoted GPU cluster, enhancing throughput per epoch as new knowledge from educational establishments necessitated frequent re-training.
To deal with knowledge privateness, Helfie implements strong AI content material security insurance policies to make sure consumer 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 stop any dangerous consumer actions.
Helfie.ai’s merchandise—Vitals AI, Respiratory AI, STI AI, and Pores and skin AI—at the moment are obtainable on Azure Market.
Devoted GPU clusters can be found for startups on Microsoft for Startups who’re backed by certainly one of Microsoft’s strategic VC companions: Microsoft expands free Azure AI infrastructure entry to startups | Microsoft for Startups Weblog, together with Startups who’re lively within the Pegasus Program.
