What Types of Testing Does Life Science Technology Demand?

 

Life science technology requires the following types of testing to ensure it safeguards data and benefits end users:

  • Performance testing: Understand how your platform performs under typical conditions and discover the stability and responsiveness of systems under standard workloads. 
  • Load testing: Understand how much traffic your platform can handle in high-traffic periods. 
  • Stress testing: See how your platform performs under extreme loads.

Comments

Post a Comment

Popular posts from this blog

Life Sciences Software - types of software used in Healthcare

Image
 Clinical gadget programming - clinical gadgets, going from imaging gear to indicative instruments, rely upon programming to precisely work. This product helps control equipment, process information, and guarantee patient security. For example, blood glucose screens use programming to catch, examine, and present basic clinical data. Telehealth stages - this product empowers far off clinical counsels and medical care administrations, which became basic during the Coronavirus pandemic's social separating. These stages work with virtual arrangements, permitting patients to associate with medical care suppliers from the solace of their homes, in this manner upgrading availability and limiting actual visits. Electronic wellbeing record (EHR) frameworks - online data sets and EHR frameworks unify patient records, therapy history, and clinical data. These frameworks further develop patient consideration coordination among medical services experts and backing effective information sharing.
Read more

How can we design better software for the life sciences?

Image
 Transparency in Information Analysis One of the main reasons for developing life science software is to automate some part of an analytical process through the use of algorithms, easing the burden on scientists. Often, most of the logic of an algorithm tends to be abstracted away from the users - it’s a ‘black box’ that no one can see into to make sense of. Information Hierarchy A major challenge in the life sciences is the scale and richness of biological data. When using software tools for accessing or manipulating large biological datasets, it is easy to become overwhelmed, miss what you are looking for, and miss opportunities for discovery. Life Sciences Software Flexible Workflows Scientific workflows can switch rapidly from the ordinary to the novel as researchers respond to signals in their data. Software interfaces need to support streamlined completion of routine tasks as well as facilitating detours for more in-depth data exploration. Encouraging Exploration of Results Scien
Read more

Smart Garments

  Emergence of intelligent fabric that can non-intrusively sense data can be extremely valuable in observing health stats like body temperature, blood pressure, pulse rate, respiration rate, movement – specially for patients, senior citizens or infants/children needing continuous care. View more   Smart garments
Read more