1. Breath Metabolomics: Breath analysis is a pivotal method for biological phenotyping. In a pilot study, 100 experiments with four subjects have been performed to study the reproducibility of this technique.
2. Breast Tissue: Dataset with electrical impedance measurements of freshly excised tissue samples from the breast.
3. Breast Cancer Coimbra: Clinical features were observed or measured for 64 patients with breast cancer and 52 healthy controls.
4. LSVT Voice Rehabilitation: 126 samples from 14 participants, 309 features. Aim: assess whether voice rehabilitation treatment lead to phonations considered 'acceptable' or 'unacceptable' (binary class classification problem).
5. Early biomarkers of Parkinsonís disease based on natural connected speech: Predict a pattern of neurodegeneration in the dataset of speech features obtained from patients with early untreated Parkinson‚Äôs disease and patients at high risk developing Parkinson‚Äôs disease.
6. Iris: Famous database; from Fisher, 1936
7. HCC Survival: Hepatocellular Carcinoma dataset (HCC dataset) was collected at a University Hospital in Portugal. It contains real clinical data of 165 patients diagnosed with HCC.
8. Divorce Predictors data set: Participants completed the ‚ÄúPersonal Information Form‚ÄĚ and ‚ÄúDivorce Predictors Scale‚ÄĚ.
9. Divorce Predictors data set: Participants completed the Personal Information Form and Divorce Predictors Scale.
10. Bone marrow transplant: children: The data set describes pediatric patients with several hematologic diseases, who were subject to the unmanipulated allogeneic unrelated donor hematopoietic stem cell transplantation.
11. Amphibians: The dataset is a multilabel classification problem. The goal is to predict the presence of amphibians species near the water reservoirs based on features obtained from GIS systems and satellite images
12. Parkinsons: Oxford Parkinson's Disease Detection Dataset
13. Breast Cancer Wisconsin (Prognostic): Prognostic Wisconsin Breast Cancer Database
14. seeds: Measurements of geometrical properties of kernels belonging to three different varieties of wheat. A soft X-ray technique and GRAINS package were used to construct all seven, real-valued attributes.
15. Daphnet Freezing of Gait: This dataset contains the annotated readings of 3 acceleration sensors at the hip and leg of Parkinson's disease patients that experience freezing of gait (FoG) during walking tasks.
16. Algerian Forest Fires Dataset : The dataset includes 244 instances that regroup a data of two regions of Algeria.
17. SPECTF Heart: Data on cardiac Single Proton Emission Computed Tomography (SPECT) images. Each patient classified into two categories: normal and abnormal.
18. Quality Assessment of Digital Colposcopies: This dataset explores the subjective quality assessment of digital colposcopies.
19. Heart failure clinical records: This dataset contains the medical records of 299 patients who had heart failure, collected during their follow-up period, where each patient profile has 13 clinical features.
20. Haberman's Survival: Dataset contains cases from study conducted on the survival of patients who had undergone surgery for breast cancer
21. Ecoli: This data contains protein localization sites
22. Exasens: This repository introduces a novel dataset for the classification of 4 groups of respiratory diseases: Chronic Obstructive Pulmonary Disease (COPD), asthma, infected, and Healthy Controls (HC).
23. Exasens: This repository introduces a novel dataset for the classification of 4 groups of respiratory diseases: Chronic Obstructive Pulmonary Disease (COPD), asthma, infected, and Healthy Controls (HC).
24. Refractive errors: Effect of life style and genetic on eye refractive errors.
25. Breast Cancer Wisconsin (Diagnostic): Diagnostic Wisconsin Breast Cancer Database
26. HCV data: The data set contains laboratory values of blood donors and Hepatitis C patients and demographic values like age.
27. Breast Cancer Wisconsin (Original): Original Wisconsin Breast Cancer Database
28. gene expression cancer RNA-Seq: This collection of data is part of the RNA-Seq (HiSeq) PANCAN data set, it is a random extraction of gene expressions of patients having different types of tumor: BRCA, KIRC, COAD, LUAD and PRAD.
29. Cervical cancer (Risk Factors): This dataset focuses on the prediction of indicators/diagnosis of cervical cancer. The features cover demographic information, habits, and historic medical records.
30. Arcene: ARCENE's task is to distinguish cancer versus normal patterns from mass-spectrometric data. This is a two-class classification problem with continuous input variables. This dataset is one of 5 datasets of the NIPS 2003 feature selection challenge.
31. MicroMass: A dataset to explore machine learning approaches for the identification of microorganisms from mass-spectrometry data.
32. Mammographic Mass: Discrimination of benign and malignant mammographic masses based on BI-RADS attributes and the patient's age.