Saykara Launches First Fully Ambient AI Healthcare Voice Assistant


Saykara today announced the release of Kara 2.0, an AI-powered healthcare assistant that further simplifies the documentation process for physicians. Now featuring Ambient Mode, Kara 2.0 is a breakthrough AI-powered voice application for healthcare, allowing physicians and patients to interact as they normally do, all while Saykara listens, transcribes to text, parses text into structured data, and intelligently completes each form in a patient's electronic health record (EHR or chart). Saykara then automatically generates a clinic note including patient history, physical, assessment, plan, orders and referrals. With the release of Ambient Mode, Saykara is the only virtual healthcare assistant that can be used passively'in the room' during physician-patient appointments with no voice commands. Ambient Mode builds on Saykara's versatility and agnosticity, allowing it to better serve up to 18 disparate healthcare specialties, including primary care, pediatrics, internal medicine, orthopedics, urology and more.

Crowdsourced Continuous Improvement of Medical Speech Recognition

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We describe a method for continuously improving the accuracy of a large-scale medical automatic speech recognizer (ASR) using a multi-step cycle involving several groups of workers. The paper will address the unique challenges of the medical domain, and discuss how automatically created and crowdsourced input data is combined to refine the ASR language models. The improvement cycle helped to decrease the original system's word error rate from 34.1% to 10.4%, which approaches the accuracy of human transcribers trained in medical transcription.

M*Modal Enhances its Artificial Intelligence Platform to Support the Epic NoteReader CDI Workflow


FRANKLIN, TN--(Marketwired - June 14, 2017) - M*Modal, a leading provider of clinical documentation and Speech Understanding solutions, announced that its artificial intelligence (AI) powered portfolio of solutions is further enhanced to also support the Epic NoteReader CDI (Clinical Documentation Improvement) module. Along with the embedded M*Modal Computer-Assisted Physician Documentation (CAPD) technology, Epic NoteReader CDI also utilizes the M*Modal CAPD infrastructure and rigorous reporting capabilities to deliver automated physician feedback. The M*Modal CAPD technology continuously analyzes the documentation and applies machine learning and clinical reasoning across the entire patient record to deliver high-value insights and suggest improvements in quality and compliance as the note is being created. Uniquely, M*Modal CAPD technology extends significantly beyond CDI feedback focused on better capturing Hierarchical Condition Categories (HCCs), Risk-Adjusted Quality Scores, etc. This extends M*Modal's collaboration with Epic on the company's cloud-based speech recognition and natural language understanding technologies.

Suki raises $20M to create a voice assistant for doctors


When trying to figure out what to do after an extensive career at Google, Motorola, and Flipkart, Punit Soni decided to spend a lot of time sitting in doctors' offices to figure out what to do next. It was there that Soni said he figured out one of the most annoying pain points for doctors in any office: writing down notes and documentation. That's why he decided to start Suki -- previously Robin AI -- to create a way for doctors to simply start talking aloud to take notes when working with patients, rather than having to put everything into a medical record system, or even writing those notes down by hand. That seemed like the lowest hanging fruit, offering an opportunity to make it easier for doctors that see dozens of patients to make their lives significantly easier, he said. "We decided we had found a powerful constituency who were burning out because of just documentation," Soni said.

Voice Recognition Software in Medical Imaging Continues to Evolve

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Voice recognition software has been shown to reduce report turnaround time and holds promise for populating and mining structured reports -- but not all radiologists are convinced. Many users still find the software cumbersome and error prone, as seen in a recent informal Diagnostic Imaging poll where 80 percent of respondents said they use it, but 30 percent of them reported frustration with the software. And radiologists have steep demands for the software, experts said. With their need for accuracy and use of complex terms, fast-talking radiologists really put the systems to the test. "Radiologists are trying to provide an enormous amount of documentation in a very short period of time, accurately, and they are experts at grinding through that workflow and process as fast as they can," said Joe Petro, senior vice president of research and development for Nuance Healthcare.