What is she best known for?
The fields of study she is best known for:
- Internal medicine
- Disease
- Surgery
Internal medicine, Physical therapy, Gerontology, Dementia and Anesthesia are her primary areas of study.
Her work focuses on many connections between Internal medicine and other disciplines, such as Cardiology, that overlap with her field of interest in Heart rate variability.
Her research integrates issues of Longitudinal study, Preferred walking speed, Population ageing, Cognition and Activities of daily living in her study of Gerontology.
Her Longitudinal study course of study focuses on Ageing and Demography.
Her Dementia study incorporates themes from Alzheimer's disease, Central nervous system disease and Stroke.
Her Anesthesia research incorporates themes from Tilt table test and Blood pressure.
Her most cited work include:
- Diagnosis and management of dementia with Lewy bodies: Third report of the DLB Consortium (3883 citations)
- Guidelines on management (diagnosis and treatment) of syncope (853 citations)
- Head-up tilt: a useful test for investigating unexplained syncope. (635 citations)
What are the main themes of her work throughout her whole career to date?
Rose Anne Kenny mostly deals with Longitudinal study, Internal medicine, Gerontology, Cardiology and Blood pressure.
In her study, Audiology is inextricably linked to Cognition, which falls within the broad field of Longitudinal study.
Her research investigates the connection between Internal medicine and topics such as Physical therapy that intersect with issues in Prospective cohort study.
Her Gerontology study frequently draws connections to other fields, such as Cohort study.
Particularly relevant to Syncope is her body of work in Cardiology.
Her Blood pressure research incorporates elements of Supine position and Anesthesia.
She most often published in these fields:
- Longitudinal study (41.41%)
- Internal medicine (30.27%)
- Gerontology (28.11%)
What were the highlights of her more recent work (between 2018-2021)?
- Longitudinal study (41.41%)
- Gerontology (28.11%)
- Internal medicine (30.27%)
In recent papers she was focusing on the following fields of study:
Her primary areas of investigation include Longitudinal study, Gerontology, Internal medicine, Blood pressure and Ageing.
Her biological study spans a wide range of topics, including Logistic regression, Demography, Cognition, Confidence interval and Depression.
The Logistic regression study combines topics in areas such as Odds ratio and Cohort.
Rose Anne Kenny combines subjects such as Dementia, Quality of life, Loneliness and Quality of life with her study of Gerontology.
Rose Anne Kenny interconnects Resting state fMRI, Frontal lobe and Cardiology in the investigation of issues within Internal medicine.
Blood pressure and Supine position are commonly linked in her work.
Between 2018 and 2021, her most popular works were:
- Editorial: low population mortality from COVID-19 in countries south of latitude 35 degrees North supports vitamin D as a factor determining severity. (127 citations)
- Vitamin D and inflammation: Potential implications for severity of Covid-19 (69 citations)
- Perspective: Vitamin D deficiency and COVID-19 severity - plausibly linked by latitude, ethnicity, impacts on cytokines, ACE2 and thrombosis. (51 citations)
In her most recent research, the most cited papers focused on:
- Internal medicine
- Disease
- Surgery
Her main research concerns Longitudinal study, Demography, Ageing, Cognition and Gerontology.
Her Longitudinal study research includes elements of Odds ratio, Logistic regression, Cohort study, Confidence interval and Depression.
Her Odds ratio study is related to the wider topic of Internal medicine.
Her Cognition research includes elements of Fear of falling, Audiology and Anxiety.
The study incorporates disciplines such as Mental health, Loneliness, Disease and Quality of life in addition to Gerontology.
In her work, Heart rate is strongly intertwined with Cardiology, which is a subfield of Orthostatic intolerance.
This overview was generated by a machine learning system which analysed the scientist’s
body of work. If you have any feedback, you can
contact us
here.
