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Machine learning – a strategic information system opportunity to strengthen healthcare

  • Gayathri Kawshali Mayadunne
  • , Yi Wang
  • University of Bedfordshire

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Hemas Holdings PLC is one of Sri Lanka’s top diversified firms, focusing on consumer, healthcare and transportation sectors (Hemas Holdings PLC, 2022). Of their many subsidiaries, Hemas Healthcare has been one of their significant ventures in the Sri Lankan business arena. Hemas Healthcare is Sri Lanka’s most significant privately owned healthcare provider, with a substantial reach across the whole Sri Lankan healthcare value chain, and is well known for its ‘The Australian Council Health Standard International’ (ACHSI) approved hospitals in Wattala and Thalawathugoda, Sri Lanka (Hemas, 2023). Furthermore, Hemas Healthcare introduced Sri Lanka’s first digital healthcare platform under the patronage of the International Finance Corporation (IFC) to provide expert healthcare about medical treatment, health education and information services via telehealth (IFC, 2020). With the introduction of the Digital Health application, Hemas Healthcare has now encountered a strategic information system (SIS) opportunity to further develop and enhance its information technology (IT) resources to strengthen its business endeavours and to gain a competitive advantage in the Sri Lankan Healthcare industry. The Digital Health application has the potential to be further developed into an IT platform where Artificial Intelligence (AI) can be integrated to provided a streamlined healthcare service. Strategies. This paper will discuss how Machine learning ( ML) can strategically strengthen digital healthcare.

Original languageEnglish
Title of host publicationAdvanced Manufacturing and Automation XIII
EditorsYi Wang, Tao Yu, Kesheng Wang
PublisherSpringer
Pages388-394
Number of pages7
ISBN (Print)9789819706648
DOIs
Publication statusPublished - 25 Feb 2024
Event13th International Workshop of Advanced Manufacturing and Automation, IWAMA 2023 - Shanghai, China
Duration: 15 Oct 202316 Oct 2023

Publication series

NameLecture Notes in Electrical Engineering
Volume1154 LNEE
ISSN (Print)1876-1100
ISSN (Electronic)1876-1119

Conference

Conference13th International Workshop of Advanced Manufacturing and Automation, IWAMA 2023
Country/TerritoryChina
CityShanghai
Period15/10/2316/10/23

Keywords

  • decision making
  • digital technology management
  • Information systems
  • IT management
  • strategic information systems management

ASJC Scopus subject areas

  • Industrial and Manufacturing Engineering

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