Update README.md

README.md

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-# Medical Transcriptions
-Medical transcription data scraped from mtsamples.com
-### Content
-This dataset contains sample medical transcriptions for various medical specialties.
-<br>
-More information can be found [here](https://www.kaggle.com/datasets/tboyle10/medicaltranscriptions?resource=download)
+# 🏥 Medical Transcriptions - Cleaned JSONL Dataset
 
-Due to data availability only transcripts for the following medical specialties were selected for the model training:
-- Surgery
-- Cardiovascular / Pulmonary
-- Orthopedic
-- Radiology
-- General Medicine
-- Gastroenterology
-- Neurology
-- Obstetrics / Gynecology
-- Urology
+This dataset is a cleaned, normalized, and strictly formatted (`JSONL`) version of the original Medical Transcriptions dataset. It has been specifically processed to be instantly ready for NLP training tasks, handling missing values, standardizing text, and structuring nested data to avoid common CSV parsing errors.
 
----
-**task_categories:**
-- text-classification
-- feature-extraction
-  
-**language:** en <br>
-**tags:** medical <br>
-**size_categories:** 1K<n<10K
+## 🔗 Code & Full Documentation (GitHub)
+Do you want to see exactly **how** this data was cleaned? 
+The complete Python source code (Jupyter Notebook) and a comprehensive technical manual in PDF ("Python per il Data Cleaning: teoria e pratica") are available on my GitHub repository:
+
+👉 **[View the Code and Documentation on GitHub](https://github.com/Bernardosalerno/Data-cleaning-and-documentation-process-full-guide)**
+
+## 🛠️ Data Processing Highlights
+* **Format:** Converted from raw CSV to validated `JSONL`.
+* **Filtering:** Removed incomplete, noisy, or excessively short clinical transcripts.
+* **Normalization:** Regex applied to clean text, handle hidden characters, and format strings.
+* **Validation:** Automated checks to guarantee 0 duplicates and 0 critical null values.
+
+## 🙏 Acknowledgements
+This dataset is a processed and refined version of the raw data originally provided by `tchebonenko/MedicalTranscriptions` (derived from MTSamples).