[{"data":1,"prerenderedAt":90},["ShallowReactive",2],{"technologies":3,"blog:5-ways-ai-for-healthcare-management-data:":7},[4],{"slug":5,"label":6},"php","PHP",{"id":8,"source":9,"title":10,"slug":11,"url":12,"excerpt":13,"image":14,"author":15,"date":16,"date_formatted":17,"categories":18,"tags":22,"content":38,"seo":39,"related":40},21779,"wordpress","5 ways AI optimizes healthcare management data","5-ways-ai-for-healthcare-management-data","\u002F5-ways-ai-for-healthcare-management-data","AI for healthcare: The radiology wing of hospital systems and diagnostic centers produces a great amount of sensitive data. But, they often lack the analytics i...","https:\u002F\u002Fyugasa.com\u002Fpublic\u002Fwp-content\u002Fuploads\u002F2021\u002F07\u002F5-ways-AI-for-healthcare-management-data.jpg","Creative Team","2021-07-23T12:04:09+00:00","July 23, 2021",[19],{"name":20,"slug":21},"AI & Chatbots","ai-chatbots",[23,26,29,32,35],{"name":24,"slug":25},"AI","ai",{"name":27,"slug":28},"Artificial Intelligence","artificial-intelligence",{"name":30,"slug":31},"Healthcare","healthcare",{"name":33,"slug":34},"Healthcare App","healthcare-app",{"name":36,"slug":37},"AI for healthcare","ai-for-healthcare","AI for healthcare: The radiology wing of hospital systems and diagnostic centers produces a great amount of sensitive data. But, they often lack the analytics infrastructure to access and examine the data efficiently. To make this available big data, radiologists are leveraging AI-based healthcare management analytics.\r\n\r\nGenerally, healthcare image data produced from high-definition examination of the human body is vast. Depending highly on human effort to parse via all of this could lead to burnout.\r\n\r\nA tired radiologist looking at their 100th image that day could introduce human error due to floppiness. \u003Ca href=\"https:\u002F\u002Ftest.yugasa.org\u002Fartificial-intelligence\u002F\">Artificial Intelligence\u003C\u002Fa> services could help resolve any issues.\r\n\r\nKLAS Research reports US healthcare organizations are enhancing expressing an interest in AI-based medical image analytics software. But, only 17% are actively controlling such projects. This interest is slowly increasing towards the important mass.\r\n\r\nThe demand for such AI-powered software solutions is unpredicted by the end of 2021. This software will change the process of revealing cardiovascular abnormalities, brain changes from different diseases, and reevaluation of ongoing treatment.\r\n\u003Ch2>\u003Cstrong>\u003Cspan style=\"color: #15a3bc\">AI for healthcare - How can AI be incorporated into the medical imaging data process?\u003C\u002Fspan>\u003C\u002Fstrong>\u003C\u002Fh2>\r\nAI, ML, and DL methods can help increase any element of the standard medical imaging workflow. They can improve analysis tools, offer information, help in PACs, and can potentially render an appropriate diagnosis.\r\n\r\nArtificial Intelligence innovation in the medical industry is a work in progress. Healthcare tool pioneers are making considerable advances using machine learning tools such as:\r\n\r\nClassification: In this Machine Learning method, data is categorized into a different number of classes over a CNN (Convolutional Neural Network) architecture.\r\n\r\nSegmentation: This tool helps the physician identify tumors and determine anomaly size. It detects anomalies and finds out their sizes by recognizing specific pixels that include them.\r\n\r\nLocalization: This ML method helps to check the specific area of the image that includes abnormality. A cardiologist can use this methodology to detect the presence of Cancerous masses easily by analyzing a small dataset.\r\n\u003Ch2>\u003Cstrong>\u003Cspan style=\"color: #15a3bc\">Here are five ways how AI for healthcare imaging analytics:\u003C\u002Fspan>\u003C\u002Fstrong>\u003C\u002Fh2>\r\n\u003Ch3>\u003Cstrong>\u003Cspan style=\"color: #15a3bc\">AI Way #1 - Medical supply spend analysis\u003C\u002Fspan>\u003C\u002Fstrong>\u003C\u002Fh3>\r\nSurgical and medical spend add up to nearly 15 % of operating costs for a health system. Significant costs identify those saving possibilities. Undoubtedly, pricing is often intentionally fuzzy by vendors, making it nearly impossible for a human to optimize.\r\n\r\nAccording to a study, 17% of users spend reduction available by streamlining the procurement process which can be done efficiently by AI for healthcare.\r\n\r\nAn AI solution can purchase orders from an ERP to compare products based on cost and results. It can recommend great products based on cost and quality. What’s more, it can analyze vendor contracts for any restrictions. Once the product changes are approved, AI can update the ERP.\r\n\u003Ch3>\u003Cstrong>\u003Cspan style=\"color: #15a3bc\">AI Way #2 - Automated inventory management\u003C\u002Fspan>\u003C\u002Fstrong>\u003C\u002Fh3>\r\nInventory management is a highly complicated process. Using stock levels, addressing backorders, or managing recalls; it’s hard enough for our human resources to simply get the required software to the patient and doctors.\r\n\r\nAI algorithms can improve predict demand, optimize inventory levels as per purchase and history, and automate the management of recalled products. Medical sectors can decrease products and save money by sizing their inventory and improving purchasing.\r\n\u003Ch3>\u003Cstrong>\u003Cspan style=\"color: #15a3bc\">AI Way #3 - Preference card standardization\u003C\u002Fspan>\u003C\u002Fstrong>\u003C\u002Fh3>\r\nHealth systems have many physician preference cards highlighting supply demand for a specific doctor and process. But it’s too time-consuming for an individual to go through a task.\r\n\r\nAI can define these cards, reviewing product combinations, to find better opportunities. Plus, the Artificial intelligence app has the capability to find all duplicate and outdated cards to clean up and streamline the records.\r\n\u003Ch3>\u003Cstrong>\u003Cspan style=\"color: #15a3bc\">AI Way#4 - Three-way matching - AI for healthcare\u003C\u002Fspan>\u003C\u002Fstrong>\u003C\u002Fh3>\r\nOn the financial side of the supply chain, AI can automate the 3-way matching process. Currently, 3-way matching makes it time-consuming and error-prone.\r\n\r\nArtificial intelligence can automate the complete process, purchase orders and receive reports to make accurate payments. It helps medical sectors improve their cash management, reduce supply payment mistakes, and save treasures employees' time.\r\n\u003Ch3>\u003Cstrong>\u003Cspan style=\"color: #15a3bc\">AI Way #5 - Integrated predictive analytics\u003C\u002Fspan>\u003C\u002Fstrong>\u003C\u002Fh3>\r\nHealthcare professionals need a way to tackles the huge amounts of supply chain data to find information that will improve care delivery and hospital economics.\r\n\r\nThey should have forecast analytics, powered by AI to collect data from all of these sources. For example, Besides Olive’s other supply chain applications, developers work on a workflow that can assess the current patient of a hospital to predict supply needs.\r\n\r\nSo, these are five ways how AI optimizes healthcare imaging analytics. So, if you are looking for a dedicated mobile app development company for a reliable AI development solution, get in touch with a mobile app development company such as Yugasa.\r\n\u003Ch2>\u003Cstrong>\u003Cspan style=\"color: #15a3bc\">How can Yugasa help in reliable AI development solutions?\u003C\u002Fspan>\u003C\u002Fstrong>\u003C\u002Fh2>\r\n\u003Ca href=\"https:\u002F\u002Ftest.yugasa.org\u002F\">Yugasa\u003C\u002Fa> is a reliable mobile app development company that has many years of experience in delivering high-quality artificial intelligence solutions.\r\n\r\nWe have a dedicated team of developers who know how to deliver the right solution by using high-quality technology. AI for healthcare, To get more information about AI solutions, you can get in \u003Ca href=\"https:\u002F\u002Ftest.yugasa.org\u002Fcontact-us\u002F\">touch with us\u003C\u002Fa>!\r\n\r\nRead More: \u003Ca href=\"https:\u002F\u002Ftest.yugasa.org\u002Fai-chatbots\u002Fthe-future-of-ai-artificial-intelligence-will-help-in-business-transformation\u002F\">THE FUTURE OF AI: HOW ARTIFICIAL INTELLIGENCE WILL HELP IN BUSINESS TRANSFORMATION?\u003C\u002Fa>",{"title":10,"description":13,"image":14},[41,57,68,79],{"id":42,"source":43,"title":44,"slug":45,"url":46,"excerpt":47,"image":48,"author":49,"date":50,"date_formatted":51,"categories":52,"tags":56},232,"laravel","How to Build a Real-Time Fan Engagement Platform for Sports and Stadium Experiences","how-to-build-a-real-time-fan-engagement-platform-for-sports-and-stadium-experiences","\u002Fblog\u002Fhow-to-build-a-real-time-fan-engagement-platform-for-sports-and-stadium-experiences","Learn how to build a sports fan engagement platform with real-time data, venue integrations, AI workflows and secure stadium operations.","https:\u002F\u002Fadmin.yugasa.com\u002Fuploads\u002Fhow-to-build-a-real-time-fan-engagement-platform-for-sports-and-stadium-experiences.png","Admin","2026-09-15T00:00:00+00:00","September 15, 2026",[53,55],{"name":54,"slug":21},"AI Chatbots",{"name":27,"slug":28},[],{"id":58,"source":43,"title":59,"slug":60,"url":61,"excerpt":62,"image":63,"author":49,"date":50,"date_formatted":51,"categories":64,"tags":67},233,"How to Scale a Mobile Learning Platform Across Learners, Teachers and Training Centres","how-to-scale-a-mobile-learning-platform-across-learners-teachers-and-training-centres","\u002Fblog\u002Fhow-to-scale-a-mobile-learning-platform-across-learners-teachers-and-training-centres","Learn how to build a resilient learning platform with multi-tenant data, offline mobile access, automation and secure enterprise operations.","https:\u002F\u002Fadmin.yugasa.com\u002Fuploads\u002Fhow-to-scale-a-mobile-learning-platform-across-learners-teachers-and-training-centres.png",[65,66],{"name":54,"slug":21},{"name":27,"slug":28},[],{"id":69,"source":43,"title":70,"slug":71,"url":72,"excerpt":73,"image":74,"author":49,"date":50,"date_formatted":51,"categories":75,"tags":78},234,"How to Preserve Customer, Order and Financial Data During Platform Migration","how-to-preserve-customer-order-and-financial-data-during-platform-migration","\u002Fblog\u002Fhow-to-preserve-customer-order-and-financial-data-during-platform-migration","Build this approach to protect records, preserve integrity and reduce cutover risk.","https:\u002F\u002Fadmin.yugasa.com\u002Fuploads\u002Fhow-to-preserve-customer-order-and-financial-data-during-platform-migration.png",[76,77],{"name":54,"slug":21},{"name":27,"slug":28},[],{"id":80,"source":43,"title":81,"slug":82,"url":83,"excerpt":84,"image":85,"author":49,"date":50,"date_formatted":51,"categories":86,"tags":89},235,"A Practical Guide to Migrating Legacy Software to a Modern Architecture","a-practical-guide-to-migrating-legacy-software-to-a-modern-architecture","\u002Fblog\u002Fa-practical-guide-to-migrating-legacy-software-to-a-modern-architecture","Learn how these services reduce migration risk through discovery, phased architecture, testing and specialist engineering support.","https:\u002F\u002Fadmin.yugasa.com\u002Fuploads\u002Fa-practical-guide-to-migrating-legacy-software-to-a-modern-architecture.png",[87,88],{"name":54,"slug":21},{"name":27,"slug":28},[],1789543817751]