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Titlebook: Risk Assessment in Oral Health; A Concise Guide for Iain L.C. Chapple,Panos N. Papapanou Book 2020 Springer Nature Switzerland AG 2020 Ris

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41#
發(fā)表于 2025-3-28 17:09:03 | 只看該作者
42#
發(fā)表于 2025-3-28 19:26:00 | 只看該作者
Leading the Oral Healthcare Team in Risk Assessmente considerable; however, it is generally accepted that dentists receive little training in leadership skills. These skills can be developed by adhering to quite straightforward models of leadership, which have been proven to be effective in many spheres of activity. This chapter discusses how such a
43#
發(fā)表于 2025-3-28 23:46:58 | 只看該作者
44#
發(fā)表于 2025-3-29 05:37:14 | 只看該作者
45#
發(fā)表于 2025-3-29 11:02:14 | 只看該作者
46#
發(fā)表于 2025-3-29 13:15:42 | 只看該作者
Risk Driven Capitation Modelsto care for more patients, thus serving the interests of all..Capitation plans should aspire to promote a dentist-patient partnership approach, with each party striving towards a longer-term objective of optimal oral health. Ongoing clinical risk assessments can support efficiency, enable effectiveness and demonstrate good outcomes.
47#
發(fā)表于 2025-3-29 16:17:42 | 只看該作者
Risk Assessment in Oral Cancerrisk factors and accurate detection of high-risk mucosal lesions provide opportunities for risk assessment in primary care, enabling the practitioner to discuss care pathways. It is important to develop prediction models and novel biomarkers to refine risk assessment and contribute to improved clinical outcomes.
48#
發(fā)表于 2025-3-29 22:39:01 | 只看該作者
49#
發(fā)表于 2025-3-30 01:06:58 | 只看該作者
Introductionin which individuals find or place themselves. Therefore, individuals can make health and lifestyle choices, but professional advice on those choices requires precise data that pertains to that individual, rather than being based on population norms; hence, the emergence of personalised and precision medicine in twenty-first century healthcare.
50#
發(fā)表于 2025-3-30 08:03:02 | 只看該作者
Causal Inference and Assessment of Risk in the Health Sciencesdels. It provides definitions of commonly used terms, and exemplifies their use. It demonstrates why causal inference is made at the population rather than the individual level, and discusses its relevance to personalized medicine and future epidemiological research.
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