Bat-Call was founded in 2016 by a team of visionary industry experts with the mission of enhancing primary diagnostics for health care professionals and patients with the world's first AI based infra-sound auscultation technology
Bat-Call, a medical technology start-up driving innovations in acoustic digital diagnostic systems, announced today that it will shift its technology to support the early detection and monitoring of COVID-19 allowing doctors to rapidly assess and diagnose patients with its artificial intelligence based smart auscultation device.
One of the cornerstones of medicine is listening to the sounds of the body (auscultation). Yet, many of the body’s sounds are currently disregarded as they are out of the audibility range, resulting in loss of valuable medical information. Diagnosis by traditional stethoscopes is highly subjective as it relies on the examiner’s auditory skills. Inaccurate auscultation can result in suboptimal patient care, unnecessary exams and increased healthcare costs.
Based on its patented AI infra-sound analysis and deep learning classification technologies, Bat-Call is providing breakthrough acoustic digital diagnostic systems, to help in the early diagnosis and management of chronic diseases such as Pneumonia, Asthma, COPD, Congestive Heart Failure, and can now support the early detection and monitoring of COVID-19 patients.
Bat-Call’s chief medical officer, Dr. Yitzhack Schwartz, states: “Bat-Call’s technology can potentially be harnessed for effective and rapid mass screening of population as well as accurate diagnosis and monitoring of quarantined COVID-19 patients without medical personnel on site, as the device classifier can indicate the condition, and if needed, transmit it remotely. This will reduce unnecessary expensive or invasive exams such as X-ray, CT, blood tests, lowering referrals to medical centers and will keep medical staff safe from infection. The growing needs for digital healthcare solutions, together with self-assessment monitoring and tele-medicine features, are now highlighted and needed more than ever with the outbreak of the COVID-19.”
Bat-Call classification algorithm achieved 90% detection accuracy of Pneumonia patients, compared to an average of 55% with traditional auscultation1. According to recent articles, it appears that 83% of COVID-19 patients had fever, 82% had coughs, 31% with breathing difficulties, and only 9% with runny nose and 8% with sore throats.
Dr. Amin Shneifi, Head of the emergency department at the Emek medical center adds, “It is of great importance to quantify and detect the progress of lung disease involvement, which causes difficulty in breathing and coughing, without the other symptoms. A technology that can monitor low frequencies of lung sounds can better detect and monitor deterioration or improvement of the disease. I have no doubt that Bat-Call’s technology can be a great tool in managing the pandemic as it can be used for diagnosing and continuous monitoring of patients and optimizing treatment.”
“Here at the Emek Medical Center we have already began collecting lung sounds of patients coming to the emergency room with suspicion of COVID-19, and also from verified patients in our coronavirus ward. As more medical centers are expected to take part in this project, and with the data collected, the company’s classifying algorithm could create a predictive tool, to facilitate diagnosis and monitoring,” Dr. Shneifi adds.
Source: Company Press Release