Software Engineering Insights

Machines have historically aided humans to maneuver several challenging tasks all through the dark ages and the industrial revolution. A decade after the Enigma machine helped the Allies win World War II,  its inventor Alan Turing posed the one question that expanded our horizons for innovation - Can machines think?

Amidst the social-distancing norms of the COVID-19 pandemic, it has become more crucial than ever to come up with innovations in remote patient care. It is no wonder that big tech conglomerates like Amazon and Microsoft are pouring capital into digital healthcare investment, with a special focus on Remote Patient Monitoring (RPM). 

Hospital-based healthcare services are not always viable when it comes to people with special health conditions or geriatric care. Issues with traveling come in the way of healthcare for this class of citizens. Additionally, lengthy hospital stays are reported to cause deterioration in certain medical conditions, especially autoimmune ailments. 

The lack of information prioritization in the current healthcare climate has put strict limits on the care that clinicians can provide. To resolve this, innovators of Electronic Health Record (EHR) systems must introduce ways to plan for a patient's health management. This blog discusses how EHR's capabilities can be optimized and extended to make this move.

Biotech and pharmaceutical companies are required to comply with regulations enforced by the US Food and Drug Administration (FDA). Among these regulations is the Current Good Manufacturing Practice (CGMP) which governs the quality control of not just manufacturing practices and facilities but also the technology components of the drug production process.

Telemedicine can simply be defined as online healthcare and diagnosis through apps and videoconferencing. It is lately becoming a widely accepted alternative to physical patient-doctor consultation. Global attention towards providing sustainable telemedicine services has exploded. This has especially been witnessed throughout the accessibility struggles faced during the COVID-19 crisis. 

Finance industry processes are becoming more foolproof and efficient due to automation. There is plenty of evidence to showcase the growing impact of Machine Learning (ML) and its wide acceptance across various use cases in capital markets.

The radiology wing of hospital systems and diagnostic centers generates an abundance of sensitive data. However, they often lack the analytics infrastructure to access and parse the data efficiently. To make the most of this available big data, radiologists are leveraging AI-based imaging analytics.