Update README.md

README.md

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+---
+language:
+- fr
+- en
+license: cc-by-4.0
+tags:
+- health
+- automatic-symptom-detection
+- automatic-diagnosis
+- medical
+annotations_creators:
+- machine-generated
+language_creators:
+- machine-generated
+pretty_name: DDXPlus Dataset
+size_categories:
+- 1K<n<10K
+source_datasets:
+- original
+task_categories:
+- tabular-classification
+task_ids:
+- multi-class-classification
+paperswithcode_id: ddxplus-dataset
+configs:
+  - config_name: default
+
+dataset_info:
+  features:
+    - name: AGE
+      dtype: int32
+    - name: SEX
+      dtype: string
+    - name: PATHOLOGY
+      dtype: string
+    - name: EVIDENCES
+      dtype: string
+    - name: INITIAL_EVIDENCE
+      dtype: string
+    - name: DIFFERENTIAL_DIAGNOSIS
+      dtype: string
+  config_name: default
+  splits:
+    - name: train
+      num_bytes: UNKNOWN
+      num_examples: UNKNOWN
+    - name: validate
+      num_bytes: UNKNOWN
+      num_examples: UNKNOWN
+    - name: test
+      num_bytes: UNKNOWN
+      num_examples: UNKNOWN
+  download_size: UNKNOWN
+  dataset_size: UNKNOWN
+
+extra_gated_prompt: "By accessing this dataset, you agree to use it solely for research purposes and not for clinical decision-making."
+extra_gated_fields:
+  Consent: checkbox
+  Purpose of use:
+    type: select
+    options:
+      - Research
+      - Educational
+      - label: Other
+        value: other
+
+train-eval-index:
+  - config: default
+    task: medical-diagnosis
+    task_id: binary-classification
+    splits:
+      train_split: train
+      eval_split: validate
+    col_mapping:
+      AGE: AGE
+      SEX: SEX
+      PATHOLOGY: PATHOLOGY
+      EVIDENCES: EVIDENCES
+      INITIAL_EVIDENCE: INITIAL_EVIDENCE
+      DIFFERENTIAL_DIAGNOSIS: DIFFERENTIAL_DIAGNOSIS
+    metrics:
+      - type: accuracy
+        name: Accuracy
+      - type: f1
+        name: F1 Score
+---
+
 # Dataset Description
 
 We are releasing under the CC-BY licence a new large-scale dataset for Automatic Symptom Detection (ASD) and Automatic Diagnosis (AD) systems in the medical domain. The dataset contains patients synthesized using a proprietary medical knowledge base and a commercial rule-based AD system. Patients in the dataset are characterized by their socio-demographic data, a pathology they are suffering from, a set of symptoms and antecedents related to this pathology, and a differential diagnosis. The symptoms and antecedents can be binary, categorical and multi-choice, with the potential of leading to more efficient and natural interactions between ASD/AD systems and patients.  To the best of our knowledge, this is the first large-scale dataset that includes the differential diagnosis, and non-binary symptoms and antecedents.