Update app.py

app.py

@@ -24,40 +24,41 @@ st.markdown("""
 st.markdown("""
 # 📚 Clinical Terminology and Ontologies 
 ## Health Vocabularies, Systems of Coding, and Databases with Bibliographies
-__Keywords__:
-    - __Clinical Terminology__: 💬 Words that doctors use to talk to each other about patients.
-    - __Ontologies for Medications and Conditions__: 📚 A fancy way of organizing knowledge about medicine and health problems.
-    - __Health Vocabularies__: 📝 A special list of words used in healthcare to talk about health issues.
-    - __Systems of Coding__: 💻 A way of giving things like sicknesses and treatments special codes, so that doctors can remember them easily.
-    - __Databases__: 🗄️ A computer system that stores information about patients, health research, and other healthcare things.
-    - __Bibliographies__: 📖 A list of books or articles that doctors use to learn about new health information.
-
-1. 1️⃣ National Library of Medicine's **RxNorm**:
+##__Keywords__:
+
+1. __Clinical Terminology__: 💬 Words that doctors use to talk to each other about patients.
+2. __Ontologies for Medications and Conditions__: 📚 A fancy way of organizing knowledge about medicine and health problems.
+3. __Health Vocabularies__: 📝 A special list of words used in healthcare to talk about health issues.
+4. __Systems of Coding__: 💻 A way of giving things like sicknesses and treatments special codes, so that doctors can remember them easily.
+5. __Databases__: 🗄️ A computer system that stores information about patients, health research, and other healthcare things.
+6. __Bibliographies__: 📖 A list of books or articles that doctors use to learn about new health information.
+
+1. ## 1️⃣ National Library of Medicine's **RxNorm**:
     - Standardized nomenclature for clinical drugs developed by NLM
     - Provides links between drug names and related information such as ingredients, strengths, and dosages
     - **Data type: controlled vocabulary**
     - Access through **NLM's RxNorm website**: https://www.nlm.nih.gov/research/umls/rxnorm/index.html
-2. 2️⃣ Centers for Medicare and Medicaid Services' Healthcare Common Procedure Coding System (HCPCS):
+2. ## 2️⃣ Centers for Medicare and Medicaid Services' Healthcare Common Procedure Coding System (HCPCS):
     - Coding system used to identify healthcare **services, procedures, and supplies**
     - Includes **codes for drugs, biologicals, and other items** used in medical care
     - **Data type: coding system**
     - Access through **CMS website**: https://www.cms.gov/Medicare/Coding/MedHCPCSGenInfo
-3. 3️⃣ Unified Medical Language System (UMLS):
+3. ## 3️⃣ Unified Medical Language System (UMLS):
     - Set of files and software tools developed by NLM for integrating and mapping biomedical vocabularies
     - Includes RxNorm and other drug vocabularies, as well as other terminologies used in medicine
     - **Data type: controlled vocabulary**
     - Access through UMLS Metathesaurus: https://www.nlm.nih.gov/research/umls/index.html
-4. 4️⃣ PubMed:
+4. ## 4️⃣ PubMed:
     - Database of **biomedical literature** maintained by the National Center for Biotechnology Information (NCBI)
     - Includes information about **drugs, including drug names, chemical structures, and pharmacological actions**
     - **Data type: bibliographic database**
     - Access through **PubMed website**: https://pubmed.ncbi.nlm.nih.gov/
-5. 5️⃣ PubChem:
+5. ## 5️⃣ PubChem:
     - Database of chemical substances maintained by NCBI
     - Includes information about drugs, including **chemical structures, properties, and activities**
     - **Data type: chemical database**
     - Access through **PubChem website**: https://pubchem.ncbi.nlm.nih.gov/
-6. 6️⃣ Behavioral Health Code Terminology Sets:
+6. ## 6️⃣ Behavioral Health Code Terminology Sets:
     - Code terminology sets specific to behavioral health
     - Includes **DSM** published by American Psychiatric Association, **ICD** published by World Health Organization, and **CPT** published by American Medical Association
     - **Data type: coding system**
@@ -65,7 +66,7 @@ __Keywords__:
         1. [DSM](https://www.psychiatry.org/psychiatrists/practice/dsm)
         2. [ICD](https://www.who.int/standards/classifications/classification-of-diseases)
         3. [CPT](https://www.ama-assn.org/practice-management/cpt/current-procedural-terminology-cpt)
-7. [Examples🩺⚕️NLP Clinical Ontology Biomedical NER](https://huggingface.co/spaces/awacke1/Biomed-NLP-AI-Clinical-Terminology)
+7. ## [Examples🩺⚕️NLP Clinical Ontology Biomedical NER](https://huggingface.co/spaces/awacke1/Biomed-NLP-AI-Clinical-Terminology)
 """)
 
 st.markdown("""
@@ -73,7 +74,7 @@ st.markdown("""
     1. 🤔 **Sentiment analysis** - Determine underlying sentiment of text.  [Example](https://huggingface.co/spaces/awacke1/Sentiment-analysis-streamlit)
     2. 📝 **Named Entity Recognition (NER)** - Identify and classify named entities in text.  [Example](https://huggingface.co/spaces/awacke1/Named-entity-resolution)
     3. 🔊 **Speech recognition** - Transcribe spoken language into text.
-    - Examples
+    # Advanced NLP Examples:
         1. https://huggingface.co/spaces/awacke1/ASR-High-Accuracy-Test
         2. https://huggingface.co/spaces/awacke1/ASRGenerateStory
         3. https://huggingface.co/spaces/awacke1/TTS-STT-Blocks
@@ -87,14 +88,14 @@ st.markdown("""
     9. 💬 **Text generation** - Generate natural language text.  [Example](https://huggingface.co/spaces/awacke1/Sentence2Paragraph)
     10. 🔎 **Topic modeling** - Automatically identify topics in a large corpus of text.  [Example](https://huggingface.co/spaces/awacke1/Topic-modeling)
     - Examples
-        1. NLP Video Summary: https://huggingface.co/spaces/awacke1/Video-Summary
-        2. TTS-STT ASR with Multiple Voices: https://huggingface.co/spaces/awacke1/TTS-STT-Blocks
-        3. NLP Transcript with Video Player: https://huggingface.co/spaces/awacke1/Streamlit-ASR-Video
-        4. NLP Clinical Ontology Biomedical NER: https://huggingface.co/spaces/awacke1/Biomed-NLP-AI-Clinical-Terminology
-        5. Document Understanding and NLP:  https://huggingface.co/spaces/awacke1/AIDocumentUnderstandingOCR
-        6. NLP ASR Wav2Vec2 Multilingual:  https://huggingface.co/spaces/awacke1/ASR-High-Accuracy-Test
-        7. Live ASR: https://huggingface.co/spaces/awacke1/ASR-SOTA-NvidiaSTTMozilla
-        8. NLP and Visualization: https://huggingface.co/spaces/awacke1/Visualization-Plotly-Sunbursts-Treemaps-and-WebGL
+        1. [NLP Video Summary](https://huggingface.co/spaces/awacke1/Video-Summary)
+        2. [TTS-STT ASR with Multiple Voices](https://huggingface.co/spaces/awacke1/TTS-STT-Blocks)
+        3. [NLP Transcript with Video Player](https://huggingface.co/spaces/awacke1/Streamlit-ASR-Video)
+        4. [NLP Clinical Ontology Biomedical NER](https://huggingface.co/spaces/awacke1/Biomed-NLP-AI-Clinical-Terminology)
+        5. [Document Understanding and NLP](https://huggingface.co/spaces/awacke1/AIDocumentUnderstandingOCR)
+        6. [NLP ASR Wav2Vec2 Multilingual](https://huggingface.co/spaces/awacke1/ASR-High-Accuracy-Test)
+        7. [Live ASR](https://huggingface.co/spaces/awacke1/ASR-SOTA-NvidiaSTTMozilla)
+        8. [NLP and Visualization](https://huggingface.co/spaces/awacke1/Visualization-Plotly-Sunbursts-Treemaps-and-WebGL)
 """)
 
 st.markdown("""