The Digital Twin Technology has been widespread in various sectors like Manufacturing, Smart Cities, Retail, Automotive, Oil & Gas, Aerospace, Mining, and Healthcare. There are huge prospects in these areas. Now in Healthcare, along with data from IoT, Digital Twin Application in Healthcare is going to play an important role in the betterment of the health and medical sector.
Faststream Technologies’s digital twin can solutions can help healthcare enterprises and healthcare professionals to point out the path to improve and streamline processes, upgrade patient experience, reduce operating costs, and augment value of care.
Our digital twin creates a physical model of spaces and processes where the cost, as well as the quality optimization parameters, are examined. The ultimate selected-based simulations leveraging the digital twin. Further, the Digital Twin Application in Healthcare can upgrade with the growing technologies like Real-Time Locating Systems, which propounds a powerful data source and a means to test changes in layout, process, etc.
By simulating an invasive clinical procedure Faststream Technologies Digital twins Solutions will help to predict the outcome before the therapy is selected. From medical device selection (position, orientation, dimension) to surgical variable determination (magnitude, angle, shape).
Faststream Technologies’ virtual twin of patients helps the physicians in Remotely monitoring patients. It uses flexible analytics and algorithms to produce accurate outcomes with continuous updating of data collection capabilities & curating. We can monitor patients through Smart Wearable. Smaller and more comfortable wearables through sensors will be used to feed with real-time data from our digital twin in the cloud. With enough understanding of disease progression and continuous patient data collection via heath trackers (biometric, behavioral, emotional, cognitive, psychosocial) Faststream can develop models that detect symptoms at early stages, giving doctors and users the capacity to diagnose the patient before getting ill. Besides, during treatment, we will be able to evaluate if the treatment is being effective.
Faststream Technologies has Created a digital twin model to apply to the hospital and administrators by which the nurses and doctors can get a vigorous, real-time analysis of insight and outsight of patients, suggesting to them a proper schedule of workflows. This helps in bringing down queue time for the patients while checking appointments and accurate inventory procedures and maintenance.
Using Artificial Intelligence, our “Digital heart twin” assists doctors in making a more precise diagnosis of how differently the medicines affect the body of patients personally. Our Technology could also be in use for determining the risk zones by analyzing the Epidemiology data to track any particular infection.
Faststream Technologies has created a virtual twin with thousands of drugs in order to point out the best one or ones for that particular case. But this does not need to stop at the drugs which already exist. Faststream can create a digital outfit of real patients with various phenotypes, which share symptoms, and test new potential drugs to anticipate which one has more chances to succeed as well as the optimal dosage. Increasing the first shoot will lower the number of clinical trials necessary in Digital Twin Application in Healthcare.
Nowadays there are high requests for Medical imaging facilities. So, due to this high request, diagnostic medical imaging is an operational challenge for suppliers around the world. How can they make the best use of space, equipment, and staff to provide feasible care for patients? The worth of a sturdy, high-fidelity simulation in this situation is clear.
Faststream Technologies are tracking the patient from check-in to reports being delivered to the patient as all the data is put to the model. Faststream proposes a very patient-centered workflow by creating a powerful model of a care facility where the provider organization can recognize and open out best practices in order to improve efficiency, patient experience, and quality of care.
The Traditional population health programs need a general definition of what is a chronic disease patient like one patient with Chronic Respiratory problems or Chronic Lungs Disease. Still, now therapeutic decision-making for a physician needs complex phenotyping mechanisms which can be invariably mapped to a drug and the dosage for a patient. This gives to the more complex which cannot become across normally in traditional chronic disease programs.
Faststream Technologies is currently working with Persistent Systems on projects where AI-augmented therapeutic decision-making is being set up under these core demands. Our population health project goes to the level of processing patients’ data to characterize a disease deeply enough to automate the choice of drugs. It is being successfully used with non-clinicians who are using AI to guide them through the choice, timing, and dosage of medicine. It is helping them manage patient populations effectively and remotely, achieving clinical goals quickly while reducing total expenditure.
Faststream Technologies patient’s digital twin Solutions feed on different health data sources like in-person measurements, imaging records, laboratory results, and genetics which will help during diagnosis. Our complete patient twin model will simulate the health status of the patient as captured from available clinical data and infer the missing parameters from statistical models. For instance, the combination of cardiovascular imaging and computational fluid dynamics enables non-invasive characterizations of flow fields and the calculation of diagnostic metrics.
Our Digital Twin can be defined as a dynamic digital replica of the patient, created with data that is historically available. It is also designed to capture data continuously from the life of that individual. Faststream’s digital twin Solutions are intended for more effective care interventions by helping clinicians and other intersecting care technologies to really “know” the patient. A digital twin data architecture dives deep to help characterize the patient’s uniqueness, such as:
Our Big data feeding into a Digital Twin is multidimensional and continues to accumulate from inputs, such as: