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Healthcare

FUTURISTIC HEALTHCARE DELIVERY

EHRs, wearable health devices play an important part in changing how medical care is delivered.

We enable hospitals to use the potential of the Internet of Things (IoT), big data analytics, and artificial intelligence (AI) to improve efficiency and patient care.

Connected Hospitals

The healthcare industry is one of the most advanced adopters of IoT technology, with around 60% of hospitals having implemented it in some form. Hospital staff who have access to real-time information from IoT sensors can use it to make their work more efficient and provide better care.

IoT integration in hospitals ushers in a lot of efficiencies, from summoning medical staff in emergencies to continuous monitoring of patients. By utilizing sensor technologies that cause the least interference with medical equipment—and ensuring safe implementation—we prioritize efficiency over all else.

Artificial Intelligence in Medical Diagnosis

Healthcare data can be in the form of structured information but also unstructured, requiring different AI approaches. Machine learning techniques are useful in analyzing imaging and genetic data; meanwhile, natural language processing methods can be used to extract information from clinical notes — which then gets fed into machine learning models.

Advanced artificial intelligence systems that use deep learning can help doctors identify diseases by improving the accuracy and speed of diagnosis.

For example, a pair of AI systems have been developed to augment the accuracy of lung cancer and heart disease diagnosis at a hospital in Oxford. Facial recognition software supplemented with machine learning is being used to analyze patient photos—then diagnose certain rare genetic diseases based on their symptoms.

Patients may also report symptoms in writing. Using artificial intelligence (AI) techniques to analyze patient data, computer software can be trained to identify patterns of illness and make a diagnosis or suggest treatment options. These technologies are being used to augment the accuracy and speed of diagnosis. For example, a pair of AI systems have been developed to augment the accuracy of lung cancer and heart disease diagnosis at a hospital in Oxford. Facial recognition software supplemented with machine learning is being used to analyze patient photos—then diagnose certain rare genetic diseases based on their symptoms. Patients may also report symptoms in writing.

Patient Self-Enablement

In recognition of the importance patients play in their own healthcare, organizations have turned to digital technologies that help facilitate self-care while improving care delivery. Healthcare providers can use data analytics, machine learning, and cloud technologies to offer patient services even when the patient is not present.

Patients enjoy receiving medical content and health tips via smartphones, wellness-tracker apps, and appointment reminders. They also like using self-service kiosks in the hospital or ambulatory monitoring solutions at home.

Healthcare Apps

TechDeva Infotech, a software solutions provider experienced in the healthcare domain, has developed self-enablement products for patients. Rather than modifying a current website for mobile platforms, we help clients adopt health technology that benefits consumers.

We can integrate mobile health applications into customer experience platforms and CRM solutions to deliver personalized care at patients’ fingertips.