{ "cells": [ { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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idnct_idmesh_termdowncase_mesh_termmesh_type
0336369685NCT04016870Infectionsinfectionsmesh-ancestor
1336369788NCT03266874Necrosisnecrosismesh-list
2336369897NCT02743455Feverfevermesh-list
3336370004NCT01683877Neoplasmsneoplasmsmesh-ancestor
4336370095NCT01268579Carcinomacarcinomamesh-list
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" ], "text/plain": [ " id nct_id mesh_term downcase_mesh_term mesh_type\n", "0 336369685 NCT04016870 Infections infections mesh-ancestor\n", "1 336369788 NCT03266874 Necrosis necrosis mesh-list\n", "2 336369897 NCT02743455 Fever fever mesh-list\n", "3 336370004 NCT01683877 Neoplasms neoplasms mesh-ancestor\n", "4 336370095 NCT01268579 Carcinoma carcinoma mesh-list" ] }, "execution_count": 12, "metadata": {}, "output_type": "execute_result" } ], "source": [ "import pandas as pd\n", "\n", "df = pd.read_csv('file_db/browse_conditions.txt', delimiter='|') # Use the appropriate delimiter if not tab-separated\n", "\n", "df.head()" ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [], "source": [ "files_to_keep = [\"brief_summaries\", \"interventions\", \"keywords\", \"browse_conditions\"]\n", "\n", "# maybe \"study_references\" \"sponsors\" \"overall_officials\" \"pending_results\" \"outcome_analyses\" \"provided_documents\" \"reported_event_totals\" \"responsible_parties\"\n", "\n" ] }, { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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nct_idsummaryintervention_nameintervention_typeintervention_descriptionkeywordsdesease_condition
0NCT03569293The objective of this study is to assess the e...[Placebo for Upadacitinib, Upadacitinib]DrugTablets taken orally once a day[Atopic Dermatitis, Upadacitinib][dermatitis, atopic, dermatitis, eczema, skin ...
2NCT03556839The study will integrate the efficacy of combi...[Atezolizumab, Bevacizumab, Cisplatin/Carbopla...DrugIntravenous Infusion[Cervix, Carcinoma, Atezolizumab][carcinoma, neoplasms, glandular and epithelia...
6NCT03526874Migraine affects 10-28% of children and adoles...[Lidocaine 4% Topical Application Cream [LMX 4...DrugRun-in Step: All subjects receive 32 mg (4 cm ...[Episodic Migraine, Headache, Nerve Block, Pai...[pain, migraine disorders, headache, headache ...
9NCT03526835This is a Phase 1/2 open-label, multi-center, ...[MCLA-158, MCLA-158 +Pembrolizumab]Drugfull-length IgG1 bispecific antibody targeting...[Bispecific antibody, First-in-human, MCLA-158...[squamous cell carcinoma of head and neck, neo...
11NCT02272751This study will aim to compare the effects of ...[Exercise, Relaxation]BehavioralThe Exercise intervention will consist of aero...[cancer survivorship, exercise, relaxation, mi...[lymphoma, neoplasms by histologic type, neopl...
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" ], "text/plain": [ " nct_id summary \\\n", "0 NCT03569293 The objective of this study is to assess the e... \n", "2 NCT03556839 The study will integrate the efficacy of combi... \n", "6 NCT03526874 Migraine affects 10-28% of children and adoles... \n", "9 NCT03526835 This is a Phase 1/2 open-label, multi-center, ... \n", "11 NCT02272751 This study will aim to compare the effects of ... \n", "\n", " intervention_name intervention_type \\\n", "0 [Placebo for Upadacitinib, Upadacitinib] Drug \n", "2 [Atezolizumab, Bevacizumab, Cisplatin/Carbopla... Drug \n", "6 [Lidocaine 4% Topical Application Cream [LMX 4... Drug \n", "9 [MCLA-158, MCLA-158 +Pembrolizumab] Drug \n", "11 [Exercise, Relaxation] Behavioral \n", "\n", " intervention_description \\\n", "0 Tablets taken orally once a day \n", "2 Intravenous Infusion \n", "6 Run-in Step: All subjects receive 32 mg (4 cm ... \n", "9 full-length IgG1 bispecific antibody targeting... \n", "11 The Exercise intervention will consist of aero... \n", "\n", " keywords \\\n", "0 [Atopic Dermatitis, Upadacitinib] \n", "2 [Cervix, Carcinoma, Atezolizumab] \n", "6 [Episodic Migraine, Headache, Nerve Block, Pai... \n", "9 [Bispecific antibody, First-in-human, MCLA-158... \n", "11 [cancer survivorship, exercise, relaxation, mi... \n", "\n", " desease_condition \n", "0 [dermatitis, atopic, dermatitis, eczema, skin ... \n", "2 [carcinoma, neoplasms, glandular and epithelia... \n", "6 [pain, migraine disorders, headache, headache ... \n", "9 [squamous cell carcinoma of head and neck, neo... \n", "11 [lymphoma, neoplasms by histologic type, neopl... " ] }, "execution_count": 14, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df_summary = pd.read_csv(\"file_db/brief_summaries.txt\", delimiter=\"|\")\n", "df_summary = df_summary.rename(columns={\"description\": \"summary\"})\n", "\n", "### create and merge intervention ###\n", "df_intervention = pd.read_csv(\"file_db/interventions.txt\", delimiter=\"|\")\n", "\n", "intervention_grouped = (\n", " df_intervention.groupby(\"nct_id\")[\"name\"].apply(list).reset_index()\n", ")\n", "intervention_grouped = intervention_grouped.rename(\n", " columns={\"name\": \"intervention_name\"}\n", ")\n", "merged_df = pd.merge(\n", " df_summary[[\"nct_id\", \"summary\"]],\n", " intervention_grouped[[\"nct_id\", \"intervention_name\"]],\n", " on=\"nct_id\",\n", ")\n", "\n", "df_intervention = df_intervention.rename(\n", " columns={\"description\": \"intervention_description\"}\n", ")\n", "\n", "merged_df = pd.merge(\n", " merged_df,\n", " df_intervention[[\"nct_id\", \"intervention_type\", \"intervention_description\"]],\n", " on=\"nct_id\",\n", ")\n", "\n", "### create and merge keywords ###\n", "df_keyword = pd.read_csv(\"file_db/keywords.txt\", delimiter=\"|\")\n", "keywords_grouped = df_keyword.groupby(\"nct_id\")[\"name\"].apply(list).reset_index()\n", "keywords_grouped = keywords_grouped.rename(columns={\"name\": \"keywords\"})\n", "\n", "merged_df = pd.merge(merged_df, keywords_grouped, on=\"nct_id\")\n", "\n", "### create and merge browse conditions\n", "df_condition = pd.read_csv(\"file_db/browse_conditions.txt\", delimiter=\"|\")\n", "conditions_grouped = (\n", " df_condition.groupby(\"nct_id\")[\"downcase_mesh_term\"].apply(list).reset_index()\n", ")\n", "conditions_grouped = conditions_grouped.rename(\n", " columns={\"downcase_mesh_term\": \"desease_condition\"}\n", ")\n", "\n", "merged_df = pd.merge(merged_df, conditions_grouped, on=\"nct_id\")\n", "\n", "merged_df = merged_df.drop_duplicates(subset=\"nct_id\")\n", "\n", "merged_df.head()" ] }, { "cell_type": "code", "execution_count": 15, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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desease_conditiontext
0[dermatitis, atopic, dermatitis, eczema, skin ...nct_id: NCT03569293\\nsummary: The objective of...
2[carcinoma, neoplasms, glandular and epithelia...nct_id: NCT03556839\\nsummary: The study will i...
6[pain, migraine disorders, headache, headache ...nct_id: NCT03526874\\nsummary: Migraine affects...
9[squamous cell carcinoma of head and neck, neo...nct_id: NCT03526835\\nsummary: This is a Phase ...
11[lymphoma, neoplasms by histologic type, neopl...nct_id: NCT02272751\\nsummary: This study will ...
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" ], "text/plain": [ " desease_condition \\\n", "0 [dermatitis, atopic, dermatitis, eczema, skin ... \n", "2 [carcinoma, neoplasms, glandular and epithelia... \n", "6 [pain, migraine disorders, headache, headache ... \n", "9 [squamous cell carcinoma of head and neck, neo... \n", "11 [lymphoma, neoplasms by histologic type, neopl... \n", "\n", " text \n", "0 nct_id: NCT03569293\\nsummary: The objective of... \n", "2 nct_id: NCT03556839\\nsummary: The study will i... \n", "6 nct_id: NCT03526874\\nsummary: Migraine affects... \n", "9 nct_id: NCT03526835\\nsummary: This is a Phase ... \n", "11 nct_id: NCT02272751\\nsummary: This study will ... " ] }, "execution_count": 15, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Concatenate all columns into one written text\n", "merged_df['text'] = merged_df.drop(columns=['desease_condition']).apply(lambda row: '\\n'.join([f\"{col}: {val}\" for col, val in row.items()]), axis=1)\n", "\n", "# Save the DataFrame to a new CSV file\n", "merged_df = merged_df[['desease_condition', 'text']]\n", "merged_df.to_csv('clinical_trials.csv', index=False)\n", "\n", "merged_df.head()" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "env", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.12.3" } }, "nbformat": 4, "nbformat_minor": 2 }