Global Number of Female Physicians Aged 45-54 Share by Country (Units (Persons)), 2023 Discover more data with ReportLinker!

This dataset is one of the sources of data visualisations available on the [Liberal Health Professionals] website(https://data.ameli.fr/pages/data-professionnels-sante-liberaux/). ### General information: The liberal health professions available in this dataset are: * the doctors (with more than twenty medical specialties); * dental surgeons** (including dentofacial orthopaedic specialists – ODF); * the women; * medical assistants with five professions: nurses, massage therapists, speech therapists, orthoptists, pedicures-podologists. They are health professionals active on 31 December of the year concerned and: * exercising their activity as a liberal; * in metropolitan France, Guadeloupe, French Guiana, Reunion, Martinique and Mayotte; * having received at least EUR 1 in fees; * whether they are contracted with the Sickness Insurance or not (when they generate a prescription reimbursed by the Sickness Insurance); * professionals in employment-retirement cumulation are counted in the workforce as long as they meet the previous conditions. This dataset presents demographic information about liberal healthcare professionals such as: *average ages: * women; * men; * global; * share of women; * share of men; * share 60 years of age and older; * share of under 60s. This dataset is complementary to the following dataset: Liberal health professionals: number and density by age group, sex and territory (department, region). Only the national level is available for this data. The data are derived from the National Health Data System (NSDS). For more information (source, field, definitions of modalities), visit the Method page of this site. ### Data update: The data proposed for download in the “Export” tab is updated every year (data from the whole of France since 2010).

Forecast: Share of Female Physicians Aged 45-54 in France 2024 - 2028 Discover more data with ReportLinker!

Forecast: Share of Female Physicians Aged 45-54 in Italy 2023 - 2027 Discover more data with ReportLinker!

Global Share of Female Practising Physicians by Country, 2023 Discover more data with ReportLinker!

BackgroundUnderstanding how governance factors such as democracy and corruption impact the healthcare workforce is crucial for achieving Universal Health Coverage (UHC). Effective health workforce planning and resource allocation are influenced by these political constructs. This study examines the relationship between democracy and corruption and key healthcare workforce metrics.MethodsA cross-sectional study was conducted using a global dataset from 2020 to 2022. The primary outcome was Physician Density (medical doctors per 10000 people). Secondary outcomes included the generalist to specialist ratio and the percentage of female physicians (% Female). Partial correlations, multivariate analysis of variance (MANOVA), and univariate analysis of variance (ANOVA) were used to analyze the relationship between workforce variables and the democracy index (DI), and corruption perception index (CPI), controlling for domestic health expenditure.ResultsData from 134 countries showed significant positive associations between both DI (r = 0.32, p = 0.004) and CPI (r = 0.43, p < 0.001) with physician density. MANOVA indicated significant multivariate effects of DI (Wilks’ Lambda = 0.8642, p = 0.013) and CPI (Wilks’ Lambda = 0.8036, p = 0.001) on the combined workforce variables. Univariate ANOVAs showed that DI (F = 6.13, p = 0.015) and CPI (F = 10.57, p = 0.002) significantly affected physician density, even after adjusting for domestic expenditure (F = 18.53, p < 0.001). However, neither DI nor CPI significantly impacted the Generalist to Specialist Ratio or % Female Physicians.DiscussionHigher levels of democracy and lower levels of corruption are associated with a greater density of medical doctors, independent of healthcare spending. Policymakers must advocate for governance reforms that support a robust healthcare workforce to support aim of universal health coverage.

Forecast: Share of Female Practising Physicians in the US 2024 - 2028 Discover more data with ReportLinker!

Aggregate indicators at the level of the country for 7 countries of the East Bloc from the areas of economy, defense, population and society.

Topics: 1. Population and society: population density; population growth from 1970 to 1978; infant mortality and life expectancy; degree of urbanization; rate of provision with running water and sanitary facilities; residential furnishings and housing conditions; hospital beds and doctors per capita; proportion of children in kindergartens; proportion of women in various branchs of the economy; religious affiliation; divorce rate; training level of the population; education expenditures; employees in technology and science; scientific book production; social mobility.

1. Economy: growth rate of the gross national product; GNP per capita; public investments; merchandise import and export; proportion of employees and proportion of production in the individual sectors of the economy; average income; meat consumption and supply of calories; trade with Comecon countries, capitalist and under-developed countries; trade deficit and foreign debt; growth of import and export as well as of income; work productivity; working hours needed for selected goods; capital intensity; provision of households with telephone, television, cars and other durable economic goods; energy import and energy use; employee-worker relationship; development of real income as well as prices; private savings; income concentration; retail trade index; hectare yields and proportion of private agriculture.

2. Military: defense expenditures; export of weapons; strength of military forces; proportion of defense expenditures in gross national product; number of disturbances and protest demonstrations; armed attacks and persons killed; sanctions of the government; internal security forces.

3. Miscellaneous: content analysis of newspapers regarding reports about human rights, disarmament, economic as well as technical cooperation and conflicts after adoption of the final agreement of Helsinki and Belgrad.

Please provide the following data regarding the prescribing of CNS stimulants and ADHD medicines (BNF 68 section 4.4) in England: • Number of patients prescribed CNS stimulants and ADHD medicines between January 2015 and January 2023 broken down by: - Month; - Age group (0-17 years, 18+ years); - Gender (Male and Female). - Chemical substance Response A copy of the information is attached. NHS Prescription Services process prescriptions for Pharmacy Contractors, Appliance Contractors, Dispensing Doctors and Personal Administration with information then used to make payments to pharmacists and appliance contractors in England for prescriptions dispensed in primary care settings (other arrangements are in place for making payments to Dispensing Doctors and Personal Administration). This involves processing over 1 billion prescription items and payments totalling over £9 billion each year. The information gathered from this process is then used to provide information on costs and trends in prescribing in England and Wales to over 25,000 registered NHS and Department of Health and Social Care users. Data Source The data source was the NHSBSA Information Services Data Warehouse. Exclusions The Data excludes: • Items not dispensed, disallowed and those returned to the contractor for further clarification. • Prescriptions prescribed and dispensed in Prisons, Hospitals and Private prescriptions. • Items prescribed but not presented for dispensing or not submitted to NHS Prescription Services by the dispenser. Time Period April 2015 to January 2023 inclusive. Patient Data is available from April 2015 onwards. Organisation Data Only items that were prescribed in England and dispensed in the community have been included. Year Month The year and month for which the claim for dispensed items has been submitted to NHSBSA. BNF Chemical Substance The nine characters at the beginning of a BNF code which specify the Chemical substance of a drug. Gender_PDS Whether an identified patient is (male or female) has been determined using the latest patient gender information held by the NHSBSA Information Services data warehouse at the time that the prescription data was loaded. Patient gender information is updated periodically - sometime after the data has been loaded - using information from NHS Personal Demographics Service (PDS). At the time that prescription data is loaded the PDS data held by NHSBSA may be incomplete or may not reflect the latest data held by PDS. Patient gender cannot be reported for prescriptions for which the NHS number could not be captured or where no corresponding PDS data is held by NHSBSA. Prescriptions used in this dataset have been limited to where the data held in the NHSBSA data Warehouse has been recorded as male or female. The following percentage of prescription items within the dataset had a recorded gender of male or female, by calendar year: 2015 (April to December) 79.36% 2016 81.66% 2017 81.69% 2018 81.72% 2019 83.97% 2020 87.83% 2021 87.65% 2022 87.56% 2023 (January) 87.56% Age Patient age is as captured on prescriptions during processing. Patients may appear in more than one age group if they have prescribing in more than one age group therefore patient counts should not be added together, and they should only be used as presented in this request. Data has been limited to prescriptions where an age has been captured, the following percentage of prescription items within the dataset had a recorded age, by calendar year;

✔️Abstract A Brain tumor is considered as one of the aggressive diseases, among children and adults. Brain tumors account for 85 to 90 percent of all primary Central Nervous System (CNS) tumors. Every year, around 11,700 people are diagnosed with a brain tumor. The 5-year survival rate for people with a cancerous brain or CNS tumor is approximately 34 percent for men and36 percent for women. Brain Tumors are classified as: Benign Tumor, Malignant Tumor, Pituitary Tumor, etc. Proper treatment, planning, and accurate diagnostics should be implemented to improve the life expectancy of the patients. The best technique to detect brain tumors is Magnetic Resonance Imaging (MRI). A huge amount of image data is generated through the scans. These images are examined by the radiologist. A manual examination can be error-prone due to the level of complexities involved in brain tumors and their properties. Application of automated classification techniques using Machine Learning (ML) and Artificial Intelligence (AI) has consistently shown higher accuracy than manual classification. Hence, proposing a system performing detection and classification by using Deep Learning Algorithms using Convolution-Neural Network (CNN), Artificial Neural Network (ANN), and Transfer-Learning (TL) would be helpful to doctors all around the world.

✔️ Context Brain Tumors are complex. There are a lot of abnormalities in the sizes and location of the brain tumor(s). This makes it really difficult for complete understanding of the nature of the tumor. Also, a professional Neurosurgeon is required for MRI analysis. Often times in developing countries the lack of skillful doctors and lack of knowledge about tumors makes it really challenging and time-consuming to generate reports from MRI’. So an automated system on Cloud can solve this problem.

✔️ Definition To Detect and Classify Brain Tumor using, CNN and TL; as an asset of Deep Learning and to examine the tumor position(segmentation).

✔️ About the data: The dataset contains 3 folders: yes, no and pred which contains 3060 Brain MRI Images.

Folder Description Yes The folder yes contains 1500 Brain MRI Images that are tumorous No The folder no contains 1500 Brain MRI Images that are non-tumorous By: Ahmed Hamada

Forecast: Share of Female Practising Physicians Aged 35 or Less in the US 2022 - 2026 Discover more data with ReportLinker!

Global Number of Female Practising Physicians Aged 35 or Less Share by Country (Units (Persons)), 2023 Discover more data with ReportLinker!

Global Share of Female Practising Physicians Aged 75+ by Country, 2023 Discover more data with ReportLinker!

BackgroundUnderstanding how governance factors such as democracy and corruption impact the healthcare workforce is crucial for achieving Universal Health Coverage (UHC). Effective health workforce planning and resource allocation are influenced by these political constructs. This study examines the relationship between democracy and corruption and key healthcare workforce metrics.MethodsA cross-sectional study was conducted using a global dataset from 2020 to 2022. The primary outcome was Physician Density (medical doctors per 10000 people). Secondary outcomes included the generalist to specialist ratio and the percentage of female physicians (% Female). Partial correlations, multivariate analysis of variance (MANOVA), and univariate analysis of variance (ANOVA) were used to analyze the relationship between workforce variables and the democracy index (DI), and corruption perception index (CPI), controlling for domestic health expenditure.ResultsData from 134 countries showed significant positive associations between both DI (r = 0.32, p = 0.004) and CPI (r = 0.43, p < 0.001) with physician density. MANOVA indicated significant multivariate effects of DI (Wilks’ Lambda = 0.8642, p = 0.013) and CPI (Wilks’ Lambda = 0.8036, p = 0.001) on the combined workforce variables. Univariate ANOVAs showed that DI (F = 6.13, p = 0.015) and CPI (F = 10.57, p = 0.002) significantly affected physician density, even after adjusting for domestic expenditure (F = 18.53, p < 0.001). However, neither DI nor CPI significantly impacted the Generalist to Specialist Ratio or % Female Physicians.DiscussionHigher levels of democracy and lower levels of corruption are associated with a greater density of medical doctors, independent of healthcare spending. Policymakers must advocate for governance reforms that support a robust healthcare workforce to support aim of universal health coverage.

Forecast: Share of Female Practising Physicians Aged 35-44 in the US 2023 - 2027 Discover more data with ReportLinker!

Forecast: Share of Female Physicians Aged 45-54 in Germany 2024 - 2028 Discover more data with ReportLinker!

Characteristics of mineral intake in the studied groups.

Forecast: Share of Female Physicians Aged 45-54 in Japan 2024 - 2028 Discover more data with ReportLinker!

Forecast: Share of Female Practising Physicians Aged 55-64 in France 2023 - 2027 Discover more data with ReportLinker!

Forecast: Share of Female Practising Physicians Aged 35-44 in Germany 2024 - 2028 Discover more data with ReportLinker!