Countries aiming to reduce their tuberculosis (TB) burden by 2035 to the levels envisaged by the World Health Organization End TB Strategy need to innovate, with approaches such as digital health (electronic and mobile health) in support of patient care, surveillance, programme management, training and communication. Alongside the large-scale roll-out required for such interventions to make a significant impact, products must stay abreast of advancing technology over time. The integration of artificial intelligence into new software promises to make processes more effective and efficient, endowing them with a potential hitherto unimaginable. Users can benefit from artificial intelligence-enabled pattern recognition software for tasks ranging from reading radiographs to adverse event monitoring, sifting through vast datasets to personalise a patient’s care plan or to customise training materials. Many experts forecast the imminent transformation of the delivery of healthcare services. We discuss how artificial intelligence and machine learning could revolutionise the management of TB.
Tuberculosis control, and the where and why of artificial intelligence / R. Doshi, D. Falzon, B.V. Thomas, Z. Temesgen, L. Sadasivan, G.B. Migliori, M. Raviglione. - In: ERJ OPEN RESEARCH. - ISSN 2312-0541. - 3:2(2017).
|Titolo:||Tuberculosis control, and the where and why of artificial intelligence|
|Parole Chiave:||Pulmonary and Respiratory Medicine|
|Settore Scientifico Disciplinare:||Settore MED/17 - Malattie Infettive|
|Data di pubblicazione:||2017|
|Digital Object Identifier (DOI):||http://dx.doi.org/10.1183/23120541.00056-2017|
|Appare nelle tipologie:||01 - Articolo su periodico|
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|ERJ Open Res 2017 Artificial Intelligence & TB.pdf||Post-print, accepted manuscript ecc. (versione accettata dall'editore)||Open Access Visualizza/Apri|