Titlebook: Information Technology & The Law; Chris Edwards (Professor of Management Information Book 1990Latest edition Chris Edwards, Nigel Savage,

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書目名稱Information Technology & The Law影響因子(影響力)學科排名




書目名稱Information Technology & The Law網(wǎng)絡公開度




書目名稱Information Technology & The Law網(wǎng)絡公開度學科排名




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書目名稱Information Technology & The Law被引頻次學科排名




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書目名稱Information Technology & The Law讀者反饋學科排名

JAUNT

Chris Edwards,Nigel Savage Further, it suggests a framework to present and evaluate POC devices used in the healthcare industry. We argue that having such a framework provides a set of measures to evaluate and select POC for various tasks. The scope of this study is limited to medical-grade devices used at home or in clinics

補助

Simon Chaltongnal. It provides a full informational assessment of health/medical data and needs more investigations for the clinical interpretation related to the diseases. This chapter briefly introduces the blood pulse signal representation by using those assessment techniques mentioned above and illustrates t

Regurgitation

Dolina B. Kayeimaging with computational modeling, which will allow for faster modeling, improved data accuracy, and earlier detection of cardiovascular and valvular anomalies. The use of machine learning will also be explored as a means of developing patient-specific diagnostic and predictive tools for character

grieve

Robert Harttored in separate locations. From a sociological perspective, federated learning represents a shift in the power dynamic between those providing and those using medical data for research. Under a federated learning framework, raw data never leaves the client’s device. Instead, the centralised server

北極人

Chris Edwards,Nigel Savagellected were analysed using a thematic approach, the quantitative data was statistically analysed. Findings showed unstandardised implementations of digital health devices and applications, disparate and intermittent network connectivity with poor quality of service, limited digital health use skill

貪心

Ian Walden,Nigel Savageariations in annual rainfall erosivity in Kazakhstan using past and future climate data. Based on the baseline climate, the average change in percent rainfall erosivity is 26.9%, 26.4%, and 35.2% in the 2030s, 2050s, and 2070s, respectively. The aggregate average annual precipitation and erosion act

Working-Memory

Trevor Cookariations in annual rainfall erosivity in Kazakhstan using past and future climate data. Based on the baseline climate, the average change in percent rainfall erosivity is 26.9%, 26.4%, and 35.2% in the 2030s, 2050s, and 2070s, respectively. The aggregate average annual precipitation and erosion act

無孔

Richard Totty,Anthony HardcastleMJ mm ha. h. year.. The magnitude of the change varies with the GCMs, with the largest change being 26.6% (508.85 MJ mm ha. h. year.), occurring in the MIROC-5 RCP8.5 scenario in the 2070s. Although annual rainfall erosivity shows a steady increase, IPSLCM5ALR (both RCPs and periods) shows a decreas

伴隨而來

David Kerrariations in annual rainfall erosivity in Kazakhstan using past and future climate data. Based on the baseline climate, the average change in percent rainfall erosivity is 26.9%, 26.4%, and 35.2% in the 2030s, 2050s, and 2070s, respectively. The aggregate average annual precipitation and erosion act