In a first for the use of artificial intelligence in healthcare, the FDA has given a green light to a program designed to help primary care doctors diagnose autism in children at an early age, potentially when interventions may have the greatest effect on their neurodevelopment. Cognoa's Canvas Dx app takes in questionnaires filled out by caregivers and information from physicians as well as video of a child interacting with others or performing tasks, before providing assistance in making a diagnosis for autism spectrum disorder either within the doctor's office or remotely. Intended for children between the ages of 18 months and five years, the machine learning software aims to help make clinical decisions faster than previous methods--which may require referrals to a specialist plus a difficult process that can take years to identify varying symptoms. According to the FDA, though autism spectrum disorder affects about 1 in 54 children, and signs may first become apparent as early as 18 months, the average age at diagnosis may be closer to four-and-a-half years old. In addition, nonwhite children, females and people from rural areas or disadvantaged socioeconomic backgrounds are often diagnosed later or missed altogether, according to Cognoa.

Pediatric behavioral health company Cognoa has received FDA De Novo classification for its autism spectrum disorder (ASD) software diagnostic aid, Canvas Dx. The ASD diagnostic tool is designed to help primary care clinicians and pediatricians evaluate and diagnose suspected cases of autism among children. It uses machine learning algorithms to analyze videos of the child's behavior and responses to questions uploaded by parents and caregivers to devise a diagnosis. Canvas Dx is indicated as an aid in the diagnosis of ASD in patients between the ages 18 months and 5 years old who are at risk of developmental delay based on concerns of a parent, caregiver or healthcare provider. It is not intended to be used as a standalone diagnostic device.

Before getting into this report, we have to inform readers that none of the companies discussed below claim to offer software that provides diagnostics, except Cognoa, which has FDA approval to call itself a diagnostic tool. We suspect this is because these companies are not legally allowed to do so. We usually don't refer to a dictionary to determine what constitutes a concept, preferring to create our own informed definitions, such as in our What is Machine Learning? The companies listed in this report seem to provide diagnostics based on that definition, but again, readers should be informed that these companies do not technically provide diagnoses for illnesses and conditions, except Cognoa. Rather, they provide information to users on their symptoms (for legal reasons).

The healthcare industry has not traditionally been considered a technology pioneer, but in spite of some built-in obstacles, medical technology companies are making strides, particularly with the use of AI tools. That's the case with Cognoa, a health IT vendor that develops apps for helping parents and clinicians diagnose autism and other child behavioral health problems. Cognoa's machine learning-based tool was recently recognized by the Food and Drug Administration as a medical device to aid in the diagnosis of autism. The company currently provides an app that is available to parents and caregivers through their employers' benefits and through a network of therapy service providers. Halim Abbas, Cognoa's chief AI officer, said AI use in healthcare has been challenging in part because privacy regulations limit what you can do with patient data, including making that personal health data less available.

Immuta, the leading provider of enterprise data management solutions for artificial intelligence (AI), today announced a new customer relationship with Cognoa, which provides an AI-based solution for pediatric behavioral health diagnostics and digital therapies. Cognoa utilizes Immuta's platform to ensure data access policies are consistently and accurately enforced across a wide variety of data sources and users driving their machine learning programs. Palo Alto, CA-based Cognoa trains algorithms to aid in the diagnosis of behavioral health conditions, including autism and ADHD, with highly sensitive data from a production database which lives in a HIPAA environment. Data privacy and security concerns are paramount for the company, and Cognoa needed a platform that would enforce data access roles, permissions, and policies beyond the standard resource or table-based control levels. Halim Abbas, Chief AI Officer, Cognoa "We have a group of very talented data scientists who build our run-time engine for diagnostics software. Our legacy practice of providing them with all of the data they required to build models, while removing the ePHI and HIPAA sensitive information, was extremely time and labor intensive. It was essential to expedite this process, and to also continue to anonymize sensitive information for reporting."

About Cognoa Cognoa develops AI-based digital diagnostics and personalized therapeutics that provide accurate, earlier diagnoses and more effective treatments to improve outcomes and lower behavioral healthcare costs. Its first clinically-validated mobile application identifies autism as early as 18 months of age, when early intervention has the greatest potential for improved lifelong outcomes, over two and half years sooner than the national average age of 4.1 years. Cognoa provides its applications to parents through their employers and benefit providers and has been used by over 250,000 families. Cognoa is working with clinicians to offer additional precision medicine applications for faster behavioral health diagnostics and more personalized therapeutics, enabling greater opportunities for life-changing outcomes.

Cognoa has gained regulatory recognition for its machine learning software as a class II diagnostic medical device for autism -- meaning the digital health startup is now positioned to submit an application for full FDA clearance. It's a first but important regulatory step for a business that was founded back in 2014, and plays in a still nascent digital health space where untested'wellness' apps are far more plentiful than medical technologies with robust data to prove out the efficacy of their interventions. Discussions with the FDA started in early 2017, says Cognoa CEO Brent Vaughan, adding that it's hoping to gain full FDA clearance this year. He says the ultimate goal for the US startup is to become a standard part of domestic health insurance-covered medical provision -- and for that FDA clearance is essential to opening the doors. We first covered the Cognoa at launch in 2014 and the following year when it was still being careful to describe its technology as a screening rather than a diagnostic system.

The impact of AI on business and the role it may play in improving efficiency of operations and driving revenue is a main focus of the research conducted at TechEmergence. However, there are also a growing number of altruistic applications of AI that are being leveraged today. The ability to identify effective and sustainable solutions for some of the world's greatest challenges such as health, education and the environment present opportunities for profit but also for positive impact on humanity. We'll conclude with some of the future implications of altruistic AI applications discussed in these three sectors. Our aim was to cover AI use cases not commonly covered in our industry verticals, use cases commonly neglected because of a small market size or a more public "good", rather than a result that could provide a tangible "ROI" for companies.) Lack of funding is a topic of debate in many public school districts across the country.

California based company Cognoa is using machine learning to detect cognitive disorders in children up to 13 months earlier than traditional diagnosis methods. The company's VP of data science, Halim Abbas, told Which-50 a machine learning approach is ideal for detecting developmental delays. "Machine learning algorithms can ingest very large numbers of historical patient records, and use them to capture incredibly subtle patterns that might indicate the presence of cognitive disorders." "Highly resilient to noise and subjectivity" the process ultimately produces models that can approximate the understanding of what constitutes autism from the many different doctors who contributed to the dataset, Abbas said. "This allows Machine Learning screeners to succeed when applied at complex assessments like autism spectrum disorder, which can present a wide and highly variant set of behavioural phenotypes." The Cognoa method is much more accessible, according to Abbas.

Autism is a clinical diagnosis. There is no one test to diagnose autism. Depending on the type of medical professional diagnosing, typically the DSM-V (standard classification of mental disorders used by mental health professionals in the U.S.) is used to diagnose by primary care physicians, neurologists, and psychiatrists. Additionally, a set of questions known as the ADI-R (Autism Diagnostic Interview-Revised) and observations in a semi-structured assessment known as the ADOS (Autism Diagnostic Observation Schedule) are typically used by developmental pediatricians. The most recent numbers show the prevalence of autism at 1 in 68 people.