AI TRANSFORMING HEALTHCARE INDUSTRIES

• Medical Imaging

Medical imagings AI legitimize physicians with further data and information that can help them diagnose particular conditions more quickly and accurately. An algorithm could be written, for example, to review a million different chest films, both with and without malignancies, and learning to spot malignancies. The goal is to enhance the care provider’s decision-making.  Today, one of the biggest problems facing physicians and clinicians in general is the overload of too much patient information to sift through. This rapid accumulation of electronic data is thanks to the advent of electronic medical records (EMRs) and the capture of all sorts of data about a patient that was not previously recorded, or at least not easily data mined. This includes imaging data, exam and procedure reports, lab values, pathology reports, waveforms, data automatically downloaded from implantable electrophysiology devices, data transferred from the imaging and diagnostics systems themselves, as well as the information entered in the EMR, admission, discharge and transfer (ADT), hospital information system (HIS) and billing software. AI will not be diagnosing patients and replacing doctors — it will be augmenting their ability to find the key, relevant data they need to care for a patient and present it in a concise, easily digestible format. In the next couple years there will be a further data explosion with the use of bidirectional patient portals, where patients can upload their own data and images to their EMRs.

• Research and Clinical Decision Support

AI for research and clinical decision support (CDS) aims to improve clinical practice and research. It is predicted that AI will play an exciting role in the future of clinical decision support technology. AI can provide recommendations and support at the time and location where the physician is making the decision, which helps the physician provide the best service possible. Physicians, pharmacists, nurses and other care providers across the continuum of care will be able to tap AI as a resource with the potential to analyze patient data in the EHR to inform and support clinical decision making. CDS vendors are working to incorporate AI and machine learning into their products to boost diagnostics, imaging, pathology imaging and radiology. In the era of AI and machine learning, it’s no surprise clinical decision support systems (CDSSs) are becoming more available to clinicians. However, the industry has yet to address the capabilities needed for an effective CDSS, which has prevented the tools from being widely adopted in clinical settings despite research that proves its abilities.

• Voice-to-Text Transcription

You must be familiar with voice-to-text, most commonly through home assistants like Alexa. Voice transcription is a craft that requires years of experience to fully capture the nuances of different accents and language quirks that people have. Moreover, languages with different dialects often require natives from a particular area to transcribe words into plain English or another language. Artificial intelligence (AI) has now caught up to this craft by offering assistance in transcription work.

 In healthcare, this technology can be used to help healthcare professionals transfer chart information into an EHR. This, in turn, helps ensure that the right information is available to be searched and used to provide additional CDS or research support. Many of these tools are also designed to be interpreted by human beings. A transcription service, for example, may start with AI that can transcribe multiple speakers and pick up on complicated conversations. Then, a human transcriptionist would review the information to ensure it was transcribed accurately. While the technology will never replace humans, it can assist us in our transcription work by offering us robots that do part of the work, which we oversee and edit for errors. Recent advancements in natural language processing (NLP) have made it easier for devices to transcribe spoken word sound clips as they can detect unique characteristics of a language, spanning multiple areas around the world, regardless of size.

• Fraud Detection

According to FBI, United States spent around $3.5 trillion or 18% of GDP on healthcare and the amount of this spending lost due to fraud, waste, and abuse (FWA) ranged between $90 billion and $330 billion. Payment fraud is an ideal use case for machine learning and artificial intelligence (AI), and has a long track record of successful use. AI with Machine Learning helps data scientists efficiently determine which transactions are most likely to be fraudulent, while significantly reducing false positives. The techniques are extremely effective in fraud prevention and detection, as they allow for the automated discovery of patterns across large volumes of streaming transactions.

If done properly, AI & Machine learning can clearly distinguish legitimate and fraudulent behaviors while adapting over time to new, previously unseen fraud tactics. This can become quite complex as there is a need to interpret patterns in the data and apply data science to continually improve the ability to distinguish normal behavior from abnormal behavior. This requires thousands of computations to be accurately performed in milliseconds. By choosing an optimal blend of AI techniques you can detect previously unseen forms of suspicious behavior while quickly recognizing the more subtle patterns of fraud that have been previously observed across billions of accounts.

• Cyber Security

Beyond these cases related to AI for Healthcare industry, there are even more ways AI technology can influence our future, and this very fact has professionals across multiple industries extremely excited for the ever-burgeoning future of artificial intelligence. From SIRI to self-driving cars, artificial intelligence (AI) is progressing rapidly. While science fiction often portrays AI as robots with human-like characteristics, AI can encompass anything from Google’s search algorithms to IBM’s Watson to autonomous weapons. Soon, it is going to be something that is used in everyday activities.

Evolution in technology and transition in a business environment constantly create more and more opportunities for the advancement and development of new software solutions that benefit the companies. We provide end-to-end software development services and solutions for any requirement of our partners and clients. Viaante’s team of experienced software development professionals understands the importance of completing the projects within budgets, on time with high quality.