These superheroes are as real as they get. They are, in fact, scientists, doctors and clinicians continuously tinkering in tech labs across Singapore. Meet the individuals facing off against some of the world’s most pressing health issues — from cancer to heart disease and diabetic retinopathy, as they harness the incredible power of Artificial Intelligence. The Hidden Layer: Healthcare Trailblazers ============== #CNAInsider #TheHiddenLayerHealthcareTrailblazersCNA #HealthTech #ArtificialIntelligence #Documentary #Singapore #Cancer #HeartDisease #Diabetics #AI SUBSCRIBE to CNA INSIDER for more informative content: Follow CNA INSIDER on: Instagram: Facebook: Website:
Philips and PathAI team up to improve breast cancer diagnosis using artificial intelligence technology in ‘big data’ pathology research. Royal Philips, a global leader in health technology, and PathAI, a company that develops artificial intelligence technology for pathology, are collaborating with the aim to develop solutions that improve the precision and accuracy of routine diagnosis of cancer and other diseases. The partnership aims to build deep learning applications in computational pathology enabling this form of artificial intelligence to be applied to massive pathology data sets to better inform diagnostic and treatment decisions. The initial focus of this effort is on developing applications to automatically detect and quantify cancerous lesions in breast cancer tissue. transcript: #ibelieve – Breast cancer is one of the largest medical problems faced today. One in eight women will be diagnosed with breast cancer at some point in their lifetime. Therefore it is an area where building new tools to more effectively diagnose the disease and cure the disease can have a major impact on a large proportion of the population. So the central mission of pathology has not change that much in the past few hundred years. It has always been to provide the most useful diagnosis for the patient. But what has changed tremendously is the amount of data at our disposal about the patient about the tissue sample including things like genomic data, transcriptome data, lots of different morphologic data types. And the goal of computational pathology is to enable pathologists to most effectively [More]