Leaf Disease

## Overview

Leaf Disease is a dataset for object detection tasks - it contains Rice Leaf Diease annotations for 1,200 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [Public Domain license](https://creativecommons.org/licenses/Public Domain).

Preliminary figures between January to September 2024 indicated that ischaemic heart disease was the leading cause of death in the Philippines. The number of people who died from this illness was estimated at 75,500. Following this, cancer resulted in the deaths of about 43,000 people. Eating habits Heart diseases have been linked to high meat consumption, among others. In the Philippines, pork has been the most consumed meat type, followed closely by chicken. While pork meat is typically produced domestically, the country also imports pork to supplement its supply. However, plant-based food has started gaining popularity among Filipinos. In fact, a 2024 survey revealed that 69 percent of surveyed Filipinos consumed plant-based products, including meat alternatives. Common diseases in the Philippines Aside from heart and cerebrovascular diseases, the Filipino population is also exposed to infections, diabetes, skin diseases, and illnesses resulting from high meat consumption. In 2020, over 700,000 Filipinos contracted acute respiratory tract infections, followed by over 400,000 diagnosed with hypertension. In areas with high exposure to rain, dengue infections and leptospirosis have also become prevalent.

Among non-communicable diseases in the Philippines in 2023, current health expenditure was highest on diseases of the genitourinary system (nephritis) at around *** billion Philippine pesos. Meanwhile, spending on oral diseases reached **** billion in that year.

Philippines PH: Cause of Death: by Non-Communicable Diseases: % of Total data was reported at 67.300 % in 2016. This records an increase from the previous number of 67.200 % for 2015. Philippines PH: Cause of Death: by Non-Communicable Diseases: % of Total data is updated yearly, averaging 66.450 % from Dec 2000 (Median) to 2016, with 4 observations. The data reached an all-time high of 67.300 % in 2016 and a record low of 56.500 % in 2000. Philippines PH: Cause of Death: by Non-Communicable Diseases: % of Total data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Philippines – Table PH.World Bank.WDI: Health Statistics. Cause of death refers to the share of all deaths for all ages by underlying causes. Non-communicable diseases include cancer, diabetes mellitus, cardiovascular diseases, digestive diseases, skin diseases, musculoskeletal diseases, and congenital anomalies.; ; Derived based on the data from WHO's Global Health Estimates.; Weighted average;

Cause of death, by non-communicable diseases (% of total) in Philippines was reported at 69.75 % in 2019, according to the World Bank collection of development indicators, compiled from officially recognized sources. Philippines - Cause of death, by non-communicable diseases (% of total) - actual values, historical data, forecasts and projections were sourced from the World Bank on July of 2025.

Current health expenditures on diseases of the geniro-urinary system (nephritis) in the Philippines amounted to about *** billion Philippine pesos in 2023 — the highest among other diseases. In comparison, health spending on dengue was lowest in that year.

Dengue is a viral disease spread by Aedes aegypti mosquitoes. It is a problem in many tropical and subtropical parts of the world including Africa, Southeast Asia, and South America. In the Philippines, the viral disease is still endemic in all regions wherein annual cases have ranged from 200,000 to 400,000.

In this dataset, the weekly cumulative confirmed cases of Dengue in the Philippines from January 1, 2017 to October 8, 2022 were collected from the Philippine Department of Health website. The Excel file has three sheets: Sheet 1 contains the raw data that was extracted from the DOH website; Sheet 2 contains the raw, computed (Δ(X_n-X_(n-1))), and imputed data that were used in building the ARIMA-GARCH and HW models; and, Sheet 3 contains the forecasts from the models considered.

The data are useful as they as they can be used to train predictive models that can produce short-term forecasts of Dengue cases in the Philippines. These data can provide dynamic information to health officials and other concerned departments and agencies for surveillance, analysis, policy making, and decision making. The data are reusable and can be used to further explore the dengue cases in the Philippines.

Cause of death, by communicable diseases and maternal, prenatal and nutrition conditions (% of total) in Philippines was reported at 24.28 % in 2019, according to the World Bank collection of development indicators, compiled from officially recognized sources. Philippines - Cause of death, by communicable diseases and maternal, prenatal and nutrition conditions (% of total) - actual values, historical data, forecasts and projections were sourced from the World Bank on July of 2025.

Vaccine-preventable diseases accounted for the highest value of the current health expenditures on infectious and parasitic diseases in the Philippines in 2023. Spending on this type of disease amounted to about 60.31 billion Philippine pesos. This was followed by spending on respiratory infections.

Philippines PH: Mortality from CVD, Cancer, Diabetes or CRD between Exact Ages 30 and 70 data was reported at 26.800 % in 2016. This records a decrease from the previous number of 26.900 % for 2015. Philippines PH: Mortality from CVD, Cancer, Diabetes or CRD between Exact Ages 30 and 70 data is updated yearly, averaging 26.900 % from Dec 2000 (Median) to 2016, with 5 observations. The data reached an all-time high of 28.400 % in 2005 and a record low of 26.800 % in 2016. Philippines PH: Mortality from CVD, Cancer, Diabetes or CRD between Exact Ages 30 and 70 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Philippines – Table PH.World Bank.WDI: Health Statistics. Mortality from CVD, cancer, diabetes or CRD is the percent of 30-year-old-people who would die before their 70th birthday from any of cardiovascular disease, cancer, diabetes, or chronic respiratory disease, assuming that s/he would experience current mortality rates at every age and s/he would not die from any other cause of death (e.g., injuries or HIV/AIDS).; ; World Health Organization, Global Health Observatory Data Repository (http://apps.who.int/ghodata/).; Weighted average;

In 2021, the leading illness in the Philippines was acute respiratory infection, with approximately 598,591 people diagnosed with this disease. This was followed by hypertension and animal bites. The morbidity rate of acute respiratory infection per hundred thousand population in the Philippines was at nearly 543.2 in that year.

Comprehensive dataset of 1 Infectious disease physicians in Camiguin, Philippines as of July, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.

WHO: COVID-2019: Number of Patients: Confirmed: To-Date: Philippines data was reported at 4,128,961.000 Person in 24 Dec 2023. This stayed constant from the previous number of 4,128,961.000 Person for 23 Dec 2023. WHO: COVID-2019: Number of Patients: Confirmed: To-Date: Philippines data is updated daily, averaging 3,026,388.000 Person from Jan 2020 (Median) to 24 Dec 2023, with 1425 observations. The data reached an all-time high of 4,173,631.000 Person in 13 Aug 2023 and a record low of 0.000 Person in 30 Jan 2020. WHO: COVID-2019: Number of Patients: Confirmed: To-Date: Philippines data remains active status in CEIC and is reported by World Health Organization. The data is categorized under High Frequency Database’s Disease Outbreaks – Table WHO.D002: World Health Organization: Coronavirus Disease 2019 (COVID-2019): by Country and Region (Discontinued).

Comprehensive dataset of 1 Infectious disease physicians in Northern Samar, Philippines as of July, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.

Project Tycho datasets contain case counts for reported disease conditions for countries around the world. The Project Tycho data curation team extracts these case counts from various reputable sources, typically from national or international health authorities, such as the US Centers for Disease Control or the World Health Organization. These original data sources include both open- and restricted-access sources. For restricted-access sources, the Project Tycho team has obtained permission for redistribution from data contributors. All datasets contain case count data that are identical to counts published in the original source and no counts have been modified in any way by the Project Tycho team, except for aggregation of individual case count data into daily counts when that was the best data available for a disease and location. The Project Tycho team has pre-processed datasets by adding new variables, such as standard disease and location identifiers, that improve data interpretability. We also formatted the data into a standard data format. All geographic locations at the country and admin1 level have been represented at the same geographic level as in the data source, provided an ISO code or codes could be identified, unless the data source specifies that the location is listed at an inaccurate geographical level. For more information about decisions made by the curation team, recommended data processing steps, and the data sources used, please see the README that is included in the dataset download ZIP file.

WHO: COVID-2019: Number of Patients: Death: To-Date: Philippines data was reported at 66,779.000 Person in 24 Dec 2023. This stayed constant from the previous number of 66,779.000 Person for 23 Dec 2023. WHO: COVID-2019: Number of Patients: Death: To-Date: Philippines data is updated daily, averaging 52,511.000 Person from Jan 2020 (Median) to 24 Dec 2023, with 1425 observations. The data reached an all-time high of 66,779.000 Person in 24 Dec 2023 and a record low of 0.000 Person in 01 Feb 2020. WHO: COVID-2019: Number of Patients: Death: To-Date: Philippines data remains active status in CEIC and is reported by World Health Organization. The data is categorized under High Frequency Database’s Disease Outbreaks – Table WHO.D002: World Health Organization: Coronavirus Disease 2019 (COVID-2019): by Country and Region (Discontinued).

Rice Disease Detection

## Overview

Rice Disease Detection is a dataset for object detection tasks - it contains Rice Disease annotations for 500 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).

Philippines PH: Mortality from CVD, Cancer, Diabetes or CRD between Exact Ages 30 and 70: Male data was reported at 32.800 NA in 2016. This records a decrease from the previous number of 32.900 NA for 2015. Philippines PH: Mortality from CVD, Cancer, Diabetes or CRD between Exact Ages 30 and 70: Male data is updated yearly, averaging 32.900 NA from Dec 2000 (Median) to 2016, with 5 observations. The data reached an all-time high of 34.400 NA in 2005 and a record low of 31.600 NA in 2000. Philippines PH: Mortality from CVD, Cancer, Diabetes or CRD between Exact Ages 30 and 70: Male data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Philippines – Table PH.World Bank.WDI: Health Statistics. Mortality from CVD, cancer, diabetes or CRD is the percent of 30-year-old-people who would die before their 70th birthday from any of cardiovascular disease, cancer, diabetes, or chronic respiratory disease, assuming that s/he would experience current mortality rates at every age and s/he would not die from any other cause of death (e.g., injuries or HIV/AIDS).; ; World Health Organization, Global Health Observatory Data Repository (http://apps.who.int/ghodata/).; Weighted average;

Age and blood pressure data from 3500+ patient charts, following the natural disaster resulting from Typhoon Haiyan in the Philippines.The Philippines Department of Health has requested that we acknowledge the data source, which is the Department of Health, Regional Office VIII, Leyte, Philippines.

BackgroundDespite an unknown cause, Kawasaki disease (KD) is currently the primary leading cause of acquired heart disease in developed countries in children and has been increasing in recent years. Research efforts have explored environmental factors related to KD, but they are still unclear especially in the tropics. We aimed to describe the incidence of KD in children, assess its seasonality, and determine its association with ambient air temperature in the National Capital Region (NCR), Philippines from January 2009 to December 2019.MethodsMonthly number of KD cases from the Philippine Pediatric Society (PPS) disease registry was collected to determine the incidence of KD. A generalized linear model (GLM) with quasi-Poisson regression was utilized to assess the seasonality of KD and determine its association with ambient air temperature after adjusting for the relevant confounders.ResultsThe majority of KD cases (68.52%) occurred in children less than five years old, with incidence rates ranging from 14.98 to 23.20 cases per 100,000 population, and a male-to-female ratio of 1.43:1. Seasonal variation followed a unimodal shape with a rate ratio of 1.13 from the average, peaking in March and reaching the lowest in September. After adjusting for seasonality and long-term trend, every one-degree Celsius increase in the monthly mean temperature significantly increased the risk of developing KD by 8.28% (95% CI: 2.12%, 14.80%). Season-specific analysis revealed a positive association during the dry season (RR: 1.06, 95% CI: 1.01, 1.11), whereas no evidence of association was found during the wet season (RR: 1.10, 95% CI: 0.95, 1.27).ConclusionWe have presented the incidence of KD in the Philippines which is relatively varied from its neighboring countries. The unimodal seasonality of KD and its linear association with temperature, independent of season and secular trend, especially during dry season, may provide insights into its etiology and may support enhanced KD detection efforts in the country.