Medical Technology Subject Research Guide: eBooks & Journals

Biotechnology, an allied subject of biology, is also associated with its neighboring subject areas, such as: biochemistry, biophysics, biostatistics, pharmacology, cell biology, molecular biology, clinical biology, genomics and proteomics and nanotechnology, which makes this subject an advanced area in medical and health sciences.

The healthcare arena has seen a shift in recent years, with more healthcare provisions being delivered or managed via electronic means. Healthcare providers can now provide patients with diagnosis, treatment, monitoring, or a prescription without ever sharing the same physical space. With so much more patient data now stored and accessed electronically, the security of this information is ever more critical to the delivery of effective and efficient healthcare services. As blockchains are resistant to modification of their data, blockchain technology therefore provides traceable and reliable security to e-Healthcare systems and services.

Smart healthcare systems, made up of advanced wearable devices, internet of things (IoT) technologies and mobile internet connectivity, allow significant medical information to be easily and regularly transmitted over public networks. Personal patient information and clinical records are stored on hospitals and healthcare centres and can be accessed remotely by healthcare workers. Due to the widespread increase in the sheer volume of medical data being collected and created all the time, it has never been more important to ensure that such information is collected, stored and processed in a reliable and secure manner.

Medical decision support systems (MDSS) are computer-based programs that analyse data within a patient's healthcare records to provide questions, prompts, or reminders to assist clinicians at the point of care. Inputting a patient's data, symptoms, or current treatment regimens into an MDSS, clinicians are assisted with the identification or elimination of the most likely potential medical causes, which can enable faster discovery of a set of appropriate diagnoses or treatment plans. Explainable AI (XAI) is a "white box" model of artificial intelligence in which the results of the solution can be understood by the users, who can see an estimate of the weighted importance of each feature on the model's predictions, and understand how the different features interact to arrive at a specific decision.