Spaces:
Sleeping
Sleeping
Kevin Wu
commited on
Commit
•
9ae2c40
0
Parent(s):
Initial
Browse files- README.md +1 -0
- prompts.py +505 -0
- requirements.txt +3 -0
- run_extraction.py +202 -0
README.md
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
A note extraction app hosted on Hugging Face Spaces.
|
prompts.py
ADDED
@@ -0,0 +1,505 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
info_prompt = """For each clinical note, extract the following fields into a structured XML format.
|
2 |
+
For each of the following fields, return the value if it exists in the notes, otherwise do not return anything between tags.
|
3 |
+
For example, if the notes mention that the patient's name is "John Doe", then the output should be <patient_name>John Doe</patient_name>.
|
4 |
+
Otherwise, if the notes do not mention the patient's name, then do not return anything between <patient_name> and </patient_name>.
|
5 |
+
Additionally, add a <reasoning> tag with the reasoning for why you chose the value you did. This reasoning should be specific to the note and the patient, and if a field is found, it should contain a brief verbatim quote from the notes that is used to justify the value.
|
6 |
+
|
7 |
+
- patient_name
|
8 |
+
- The patient's full name (first and last name).
|
9 |
+
- For example:
|
10 |
+
<patient_name>
|
11 |
+
<reasoning>[REASONING]</reasoning>
|
12 |
+
<first_name>John</first_name>
|
13 |
+
<last_name>Doe</last_name>
|
14 |
+
</patient_name>
|
15 |
+
- date_of_birth
|
16 |
+
- The patient's date of birth in the format YYYY-MM-DD.
|
17 |
+
- For example:
|
18 |
+
<date_of_birth>
|
19 |
+
<reasoning>[REASONING]</reasoning>
|
20 |
+
<date>1990-01-01</date>
|
21 |
+
</date_of_birth>
|
22 |
+
- sex
|
23 |
+
- The patient's sex (M or F).
|
24 |
+
- For example:
|
25 |
+
<sex>
|
26 |
+
<reasoning>[REASONING]</reasoning>
|
27 |
+
<sex>M</sex>
|
28 |
+
</sex>
|
29 |
+
- traditional_chemo
|
30 |
+
- Any traditional chemotherapy drugs the patient has taken or has been prescribed.
|
31 |
+
- Within the tags, put a list of all the traditional chemotherapy drugs the patient has taken or has been prescribed as well as the date, if specified.
|
32 |
+
- For example:
|
33 |
+
<traditional_chemo_any_time>
|
34 |
+
<reasoning>[REASONING]</reasoning>
|
35 |
+
<drug>Doxorubicin/Adriamycin</drug>
|
36 |
+
<date>2021-01-01</date>
|
37 |
+
</traditional_chemo_any_time>
|
38 |
+
- The following are the traditional chemotherapy drugs you should look for:
|
39 |
+
- Doxorubicin/Adriamycin
|
40 |
+
- Carboplatin
|
41 |
+
- Vinblastine
|
42 |
+
- Chlorambucil/Leukeran
|
43 |
+
- Lomustine/CCNU
|
44 |
+
- Mitoxantrone
|
45 |
+
- Cyclophosphamide/Cytoxan
|
46 |
+
- Vinorelbine
|
47 |
+
- Vincristine
|
48 |
+
- CHOP protocol
|
49 |
+
- Actinomycin
|
50 |
+
- VAC Protocol
|
51 |
+
- Tanovea
|
52 |
+
- L-asparaginase
|
53 |
+
- Melphalan
|
54 |
+
- Satraplatin
|
55 |
+
- Epirubicin
|
56 |
+
- Neoplasene
|
57 |
+
- MOPP Chemotherapy
|
58 |
+
- Satraplatin metronomic
|
59 |
+
- Gemcitabine/Gemzar
|
60 |
+
- Fluorouracil (5-FU)
|
61 |
+
- Laverdia
|
62 |
+
- Temodar
|
63 |
+
- Unspecified traditional chemo
|
64 |
+
- No Traditional Chemo to-date
|
65 |
+
- No traditional chemo reported - validated
|
66 |
+
- Tamozolamide/Temodar
|
67 |
+
- Unknown
|
68 |
+
- Cisplatin
|
69 |
+
- Mustargen
|
70 |
+
- Procarbazine
|
71 |
+
- Mitotane
|
72 |
+
|
73 |
+
- other_cancer_treatments
|
74 |
+
- Any other cancer treatments the patient has taken or has been prescribed, according to the list provided below.
|
75 |
+
- Within the tags, put a list of all the other cancer treatments the patient has taken or has been prescribed as well as the date, if specified.
|
76 |
+
- For example:
|
77 |
+
<other_cancer_treatments>
|
78 |
+
<reasoning>[REASONING]</reasoning>
|
79 |
+
<treatment>Radiation Therapy</treatment>
|
80 |
+
<date>2021-01-01</date>
|
81 |
+
</other_cancer_treatments>
|
82 |
+
- The following are the other cancer treatments you should look for:
|
83 |
+
- Radiation Therapy
|
84 |
+
- Palladia/Toceranib
|
85 |
+
- Melanoma Vaccine (Oncept)
|
86 |
+
- Electrochemotherapy
|
87 |
+
- Masatinib
|
88 |
+
- Autologous Vaccine/Torigen/Ardent
|
89 |
+
- Lapatinib
|
90 |
+
- I'm Yunity
|
91 |
+
- Yunnan Baiyao
|
92 |
+
- Previcox
|
93 |
+
- Yale Vaccine
|
94 |
+
- Rapamycin
|
95 |
+
- Listeria Vaccine
|
96 |
+
- Imatinib
|
97 |
+
- Trametinib
|
98 |
+
- Zoledronate
|
99 |
+
- Dexrazoxane/Zinecard
|
100 |
+
- Firocoxib
|
101 |
+
- Olaparib
|
102 |
+
- Dasatinib
|
103 |
+
- Vorinostat
|
104 |
+
- Mistletoe Therapy
|
105 |
+
- EGFR Vaccine
|
106 |
+
- No other cancer treatments reported - validated
|
107 |
+
- Palbociclib
|
108 |
+
- No other cancer treatments reported to-date
|
109 |
+
- Sorafenib
|
110 |
+
- Nanoparticle Infusion
|
111 |
+
- Nanoparticle Laser
|
112 |
+
- Laser Therapy
|
113 |
+
- Stelfonta
|
114 |
+
- Tanovea
|
115 |
+
- T-Cell infusions
|
116 |
+
- Losartan
|
117 |
+
- Naltrexone
|
118 |
+
- Immunoregulin
|
119 |
+
- Papilloma Vaccine
|
120 |
+
- Gilvetmab
|
121 |
+
- Unknown
|
122 |
+
|
123 |
+
- other_conmeds
|
124 |
+
- Any other concomitant medications the patient has taken or has been prescribed.
|
125 |
+
- Within the tags, put a list of all the other concomitant medications the patient has taken or has been prescribed as well as the date, if specified.
|
126 |
+
- For example:
|
127 |
+
<other_conmeds>
|
128 |
+
<reasoning>[REASONING]</reasoning>
|
129 |
+
<medication>Aspirin</medication>
|
130 |
+
<date>2021-01-01</date>
|
131 |
+
</other_conmeds>
|
132 |
+
- The following are the other concomitant medications you should look for:
|
133 |
+
- Piroxicam
|
134 |
+
- Gabapentin
|
135 |
+
- Carprofen/Rimadyl
|
136 |
+
- Denamarin
|
137 |
+
- Ursodiol
|
138 |
+
- Clavamox
|
139 |
+
- Cerenia/Maropitant
|
140 |
+
- Ondansetron/Zofran
|
141 |
+
- Meloxicam/Metacam
|
142 |
+
- Pimobendan/Vetmedin
|
143 |
+
- Losartan/Cozaar
|
144 |
+
- Capromorelin/Entyce
|
145 |
+
- Cetirizine/Zyrtec
|
146 |
+
- Tacrolimus
|
147 |
+
- Codeine
|
148 |
+
- Telmisartan
|
149 |
+
- Buprenorphine
|
150 |
+
- Apoquel/Oclacitinib
|
151 |
+
- Imuquin
|
152 |
+
- Amlodipine
|
153 |
+
- Loratadine/Claritin
|
154 |
+
- Benazepril
|
155 |
+
- Metronidazole/Flagyl
|
156 |
+
- Prednisone
|
157 |
+
- Adequan
|
158 |
+
- Convenia
|
159 |
+
- B12 Injections
|
160 |
+
- Cisapride
|
161 |
+
- Budesonide
|
162 |
+
- Hepatoclear
|
163 |
+
- Dasaquin
|
164 |
+
- Cytopoint Injections
|
165 |
+
- Glucosamine
|
166 |
+
- Famotidine/Pepcid
|
167 |
+
- Fish Oil
|
168 |
+
- Omeprazole/Prilosec
|
169 |
+
- Mirtazapine
|
170 |
+
- Meclizine
|
171 |
+
- Amantadine
|
172 |
+
- Cortisone
|
173 |
+
- Pentoxifylline
|
174 |
+
- Ligaplex
|
175 |
+
- Reishi Mushroom
|
176 |
+
- Immune Builder
|
177 |
+
- CAS Multimushroom
|
178 |
+
- Ketamine Injections
|
179 |
+
- Vitamin E
|
180 |
+
- Trazadone
|
181 |
+
- Phenobarbitol
|
182 |
+
- Tylan Powder
|
183 |
+
- Temaril-P
|
184 |
+
- Acepromazine
|
185 |
+
- Sulfasalazine
|
186 |
+
- Keppra
|
187 |
+
- Turkey Tail Mushroom
|
188 |
+
- Furosemide/Lasix
|
189 |
+
- Tramadol
|
190 |
+
- Ciprofloxacin
|
191 |
+
- Trilostane
|
192 |
+
- Naturvet Vitapet Vitamins
|
193 |
+
- Glycoflex
|
194 |
+
- Entederm
|
195 |
+
- Aluminum Hydroxide
|
196 |
+
- Deramaxx
|
197 |
+
- Doxycycline
|
198 |
+
- Sulcrafate
|
199 |
+
- Diphenhydramine
|
200 |
+
- Fluoxetine
|
201 |
+
- Nexgard
|
202 |
+
- Reglan/Metoclopramide
|
203 |
+
- Thyroxine
|
204 |
+
- Clindamycin
|
205 |
+
- Cephalexin
|
206 |
+
- Enalapril
|
207 |
+
- CBD
|
208 |
+
- Denosyl
|
209 |
+
- Galliprant
|
210 |
+
- Methadone
|
211 |
+
- Cobalequin
|
212 |
+
- Azodyl
|
213 |
+
- FortiFlora
|
214 |
+
- Propectalin Paste
|
215 |
+
- Dexamethasone
|
216 |
+
- Ampicillin
|
217 |
+
- Coriolus mushroom
|
218 |
+
- Oxycodone
|
219 |
+
- Cyproheptadine
|
220 |
+
- Sotalol
|
221 |
+
- Enrofloxacin/Baytril
|
222 |
+
- Amiikacin
|
223 |
+
- Misoprostol
|
224 |
+
- Chlorhexadine
|
225 |
+
- Neomycin
|
226 |
+
- Visbiome
|
227 |
+
- Tranexamic Acid
|
228 |
+
- Proin
|
229 |
+
- Tobramycin
|
230 |
+
- Avmaquin
|
231 |
+
- Cosyntropin (Cortosyn)
|
232 |
+
- Vetoryl
|
233 |
+
- Metoclopromide
|
234 |
+
- Phenylpropanolamine HCl
|
235 |
+
- Cosequin
|
236 |
+
- Osteoflex
|
237 |
+
- Hepato TruBenefits
|
238 |
+
- Rx Clay
|
239 |
+
- Metamucil Powder
|
240 |
+
- Osteo-Tru Benefits
|
241 |
+
- Oat Glycerite
|
242 |
+
- Cholodin
|
243 |
+
- Proviable
|
244 |
+
- Supplements
|
245 |
+
- Wuffles Joint Supplement
|
246 |
+
- Firocoxib/Previcox
|
247 |
+
- Tylosin
|
248 |
+
- Barium Suspension
|
249 |
+
- Optimmune Ointment
|
250 |
+
- NeoPolyDex Solution
|
251 |
+
- Endosorb
|
252 |
+
- Augmentin
|
253 |
+
- Butorphanol/Dolorex
|
254 |
+
- Prazosin
|
255 |
+
- Traumeel/T-Relief
|
256 |
+
- Deracoxib
|
257 |
+
- Triamcinolone
|
258 |
+
- Probiotic
|
259 |
+
- Hydrocodone
|
260 |
+
- Lactulose
|
261 |
+
- Methocarbamol
|
262 |
+
- Cranberry Pills
|
263 |
+
- Eye Meds
|
264 |
+
- Levothyroxine
|
265 |
+
- Calcitriol
|
266 |
+
- TMS trimethoprim sulfamethoxazole
|
267 |
+
- Allergy Antigen Injections
|
268 |
+
- Propranolol
|
269 |
+
- Flexadin
|
270 |
+
- Interceptor
|
271 |
+
- Thorn SAT
|
272 |
+
- Megaflora
|
273 |
+
- Pregabalin
|
274 |
+
- Canalevia
|
275 |
+
- Cefpodoxime
|
276 |
+
- Melatonin
|
277 |
+
- Phenylephrine
|
278 |
+
- Amoxicillin
|
279 |
+
- Arnica/T-Relief
|
280 |
+
- Aminocaproic Acid
|
281 |
+
- Fluconazole
|
282 |
+
- Gastrafate
|
283 |
+
- Silver Sulfadiazine
|
284 |
+
- Mupirocin
|
285 |
+
- Marbofloxacin/Zeniquin
|
286 |
+
- Psyllium Husk
|
287 |
+
- Chlorpheniramine
|
288 |
+
- Tagamet
|
289 |
+
- Multi-vitamin
|
290 |
+
- D-mannose/cranberry
|
291 |
+
- Darbepoetin
|
292 |
+
- Soloxine
|
293 |
+
- Thuja Occidentalis
|
294 |
+
- Pantoprazole
|
295 |
+
- Normosol-R
|
296 |
+
- Nitrofurantoin
|
297 |
+
- Sildenafil
|
298 |
+
- Hydromorphone
|
299 |
+
- Terbinafine
|
300 |
+
- Sucralfate
|
301 |
+
- Clopidogrel
|
302 |
+
- EndoBlend
|
303 |
+
- Omega Benefts
|
304 |
+
- Dexmedetomidine
|
305 |
+
- Levetiracetam
|
306 |
+
- Diethylstilbesterol
|
307 |
+
- Nattokinase
|
308 |
+
- D3 supplement
|
309 |
+
- Modified Chai Hu Jia Long Gu Mu Li Tang supplement
|
310 |
+
- Power mushrooms
|
311 |
+
- super greens supplement
|
312 |
+
- Sertraline/Zoloft
|
313 |
+
- Mushroom Supplement
|
314 |
+
- Simparica Trio/Sarolaner, moxidectin, and pyrantel
|
315 |
+
- 5DMM
|
316 |
+
- Joint Supplements
|
317 |
+
- Vetericyn
|
318 |
+
- Milk Thistle
|
319 |
+
- S-Adenosyl methionine
|
320 |
+
- Cimetidine
|
321 |
+
- Silver Entro Dex
|
322 |
+
- Desmopressin
|
323 |
+
- Alpha lipoic acid
|
324 |
+
- Unasyn
|
325 |
+
- Panacur/Fenbendazole
|
326 |
+
- Xiao Chai Hu Tang
|
327 |
+
- Incurin
|
328 |
+
- Dextrose
|
329 |
+
- Fresh Frozen Plasma
|
330 |
+
- Pamidronate Infusion
|
331 |
+
- Curcumin
|
332 |
+
- Diazoxide
|
333 |
+
- Clavacillin
|
334 |
+
- Tetracycline
|
335 |
+
- B9 Folic Acid
|
336 |
+
- Prednisolone
|
337 |
+
- Cyclosporine
|
338 |
+
- Ketaconazole
|
339 |
+
- Novolin-N
|
340 |
+
- Zonisamide
|
341 |
+
- Gentamicin/Phenylephrine nasal drops
|
342 |
+
- Stool Softener
|
343 |
+
- Amitriptyline
|
344 |
+
- Moxifloxacin
|
345 |
+
- Gemfibrozil
|
346 |
+
- Taurine
|
347 |
+
- Mometamax
|
348 |
+
- Heartgard
|
349 |
+
- Green Lipped Mussel Powder
|
350 |
+
- Chlorella Powder
|
351 |
+
- BioSponge
|
352 |
+
- Folate
|
353 |
+
- Cobalamine
|
354 |
+
- Diazepam
|
355 |
+
- GenOne
|
356 |
+
- Phenoxybenzamine
|
357 |
+
- Flumethrin and Imidacloprid/Seresto
|
358 |
+
- Forte Ion Gut Health
|
359 |
+
- Dispel Stasis
|
360 |
+
- Blood Remaker + Immune Support with Mushrooms
|
361 |
+
- Pet Tab
|
362 |
+
- Omega 3 Supplement
|
363 |
+
- PIQRAY/Alpelisib
|
364 |
+
- Vitamin K
|
365 |
+
- Quadriplex
|
366 |
+
- Colchicine
|
367 |
+
- Thyro-Tabs
|
368 |
+
- Alprazolam/Xanax
|
369 |
+
- Spironolactone
|
370 |
+
- Vetstarch
|
371 |
+
- Enoxaparin
|
372 |
+
- Diclofenac/Voltaren
|
373 |
+
- Routin
|
374 |
+
- Doxepin
|
375 |
+
- Erythromycin
|
376 |
+
- Keterolac
|
377 |
+
- Tromethamine
|
378 |
+
- Cyclosporine/Atopica
|
379 |
+
- Pantoea agglomerans
|
380 |
+
- Oxybutynin
|
381 |
+
- Amikacin
|
382 |
+
- Levemir
|
383 |
+
- Apocaps
|
384 |
+
- Life Gold
|
385 |
+
- Red Clover Blossoms powder
|
386 |
+
- Modified Citrus Pectin
|
387 |
+
- Epinephrine
|
388 |
+
- Vitamin C
|
389 |
+
- Azathioprine
|
390 |
+
- RBC Transfusion
|
391 |
+
- Bactrim/sulfamethoxazole & trimethoprim
|
392 |
+
- Pet ReLeaf
|
393 |
+
- NeoPolyBac Ophthalmic
|
394 |
+
- Antibiotics (unspecified)
|
395 |
+
- Azithromycin
|
396 |
+
- Alendronate
|
397 |
+
- Cafazolin
|
398 |
+
- Diltiazem
|
399 |
+
- Mexiletine
|
400 |
+
- Pure IP6
|
401 |
+
- VetInsulin
|
402 |
+
- Herbal Supplements
|
403 |
+
- San Qi Formula
|
404 |
+
- Amnivast
|
405 |
+
- Crananidin
|
406 |
+
- Movoflex
|
407 |
+
- Lidocaine
|
408 |
+
- Tamsulosin/Flowmax
|
409 |
+
- Bedinvetmab/Librela
|
410 |
+
- Calcium Carbonate/Tums
|
411 |
+
- Dermatrophin
|
412 |
+
- Temozolomide
|
413 |
+
- Midazolam
|
414 |
+
- Anipryl
|
415 |
+
- Theophylline
|
416 |
+
- Sodium Bicarbonate
|
417 |
+
- RenaKare
|
418 |
+
- Hydroxazine
|
419 |
+
- Zincard/Dexrazoxane
|
420 |
+
- Animax
|
421 |
+
- Pro-Pectalin
|
422 |
+
- Ellevet CHews
|
423 |
+
- Cordyceps
|
424 |
+
- Benadryl
|
425 |
+
- Albon
|
426 |
+
- Robenacoxib (Onsior)
|
427 |
+
- Lysine
|
428 |
+
- Myos muscle building supplement
|
429 |
+
- Iron injections
|
430 |
+
- Xyzal (L-Cefirizine)
|
431 |
+
- Clavacillin
|
432 |
+
- Loperamide
|
433 |
+
- Theracurmin
|
434 |
+
- Quercetin Phytosome
|
435 |
+
- Anti-Neoplasia
|
436 |
+
- Fiber Supplement
|
437 |
+
- Zinc Supplement
|
438 |
+
- surgery
|
439 |
+
- Whether surgical resection of the tumor was performed.
|
440 |
+
- For example:
|
441 |
+
<surgery>
|
442 |
+
<reasoning>[REASONING]</reasoning>
|
443 |
+
<resection>Yes</resection>
|
444 |
+
</surgery>
|
445 |
+
- surgery_outcome
|
446 |
+
- The outcome of the surgery.
|
447 |
+
- For example:
|
448 |
+
<surgery_outcome>
|
449 |
+
<reasoning>[REASONING]</reasoning>
|
450 |
+
<outcome>Complete Resection</outcome>
|
451 |
+
</surgery_outcome>
|
452 |
+
- The following are the possible outcomes of the surgery:
|
453 |
+
- Completely Excised
|
454 |
+
- Incompletely Excised
|
455 |
+
- Unknown
|
456 |
+
- metastasis_at_time_of_diagnosis
|
457 |
+
- Whether the cancer has spread to other parts of the body.
|
458 |
+
- For example:
|
459 |
+
<metastasis_at_time_of_diagnosis>
|
460 |
+
<metastasis>Yes</metastasis>
|
461 |
+
</metastasis_at_time_of_diagnosis>
|
462 |
+
- The following are the possible outcomes of the surgery:
|
463 |
+
- Yes
|
464 |
+
- No
|
465 |
+
- Unknown
|
466 |
+
|
467 |
+
- compounding_pharmacy
|
468 |
+
- If a compounding pharmacy is listed, extract the name of the pharmacy. Do not include "fidocure" as a pharmacy name.
|
469 |
+
- For example:
|
470 |
+
<compounding_pharmacy>
|
471 |
+
<reasoning>[REASONING]</reasoning>
|
472 |
+
<pharmacy>CVS Pharmacy</pharmacy>
|
473 |
+
</compounding_pharmacy>
|
474 |
+
|
475 |
+
- adverse_effects
|
476 |
+
- Any adverse effects the patient has experienced from the medications. For each adverse effect, extract the following fields:
|
477 |
+
- The name of the medication
|
478 |
+
- The dosage of the medication
|
479 |
+
- The date the adverse effect started
|
480 |
+
- A description of the adverse effect
|
481 |
+
- For example:
|
482 |
+
<adverse_effects>
|
483 |
+
<reasoning>[REASONING]</reasoning>
|
484 |
+
<medication>Doxorubicin/Adriamycin</medication>
|
485 |
+
<dosage>20 mg/kg</dosage>
|
486 |
+
<date>2021-01-01</date>
|
487 |
+
<description>Nausea</description>
|
488 |
+
</adverse_effects>
|
489 |
+
|
490 |
+
- date_of_death
|
491 |
+
- The date of death of the patient, if it is known.
|
492 |
+
- For example:
|
493 |
+
<date_of_death>
|
494 |
+
<reasoning>[REASONING]</reasoning>
|
495 |
+
<date>2021-01-01</date>
|
496 |
+
</date_of_death>
|
497 |
+
|
498 |
+
- weight
|
499 |
+
- The weight of the patient, if it is known. Convert all weights to kilograms.
|
500 |
+
- For example:
|
501 |
+
<weight>
|
502 |
+
<reasoning>[REASONING]</reasoning>
|
503 |
+
<weight>20 kg</weight>
|
504 |
+
</weight>
|
505 |
+
"""
|
requirements.txt
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
gradio
|
2 |
+
openai
|
3 |
+
pandas
|
run_extraction.py
ADDED
@@ -0,0 +1,202 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
import glob
|
2 |
+
import json
|
3 |
+
import os
|
4 |
+
import time
|
5 |
+
import gradio as gr
|
6 |
+
from openai import OpenAI
|
7 |
+
|
8 |
+
import xml.etree.ElementTree as ET
|
9 |
+
import re
|
10 |
+
import pandas as pd
|
11 |
+
import api_keys
|
12 |
+
|
13 |
+
import note_extraction.hf_hosting.prompts as prompts
|
14 |
+
|
15 |
+
client = OpenAI(api_key=api_keys.OPENAI_API_KEY)
|
16 |
+
|
17 |
+
model_name = "gpt-4o-2024-08-06"
|
18 |
+
|
19 |
+
demo = client.beta.assistants.create(
|
20 |
+
name="Information Extractor",
|
21 |
+
instructions="Extract information from this note.",
|
22 |
+
model=model_name,
|
23 |
+
tools=[{"type": "file_search"}],
|
24 |
+
)
|
25 |
+
|
26 |
+
def parse_xml_response(xml_string: str) -> pd.DataFrame:
|
27 |
+
"""
|
28 |
+
Parse the XML response from the model and extract all fields into a dictionary,
|
29 |
+
then convert it to a pandas DataFrame with a nested index.
|
30 |
+
"""
|
31 |
+
# Extract only the XML content between the first and last tags
|
32 |
+
xml_content = re.search(r'<.*?>.*</.*?>', xml_string, re.DOTALL)
|
33 |
+
if xml_content:
|
34 |
+
xml_string = xml_content.group(0)
|
35 |
+
else:
|
36 |
+
print("No valid XML content found.")
|
37 |
+
return pd.DataFrame()
|
38 |
+
|
39 |
+
try:
|
40 |
+
root = ET.fromstring(xml_string)
|
41 |
+
except ET.ParseError as e:
|
42 |
+
print(f"Error parsing XML: {e}")
|
43 |
+
return pd.DataFrame()
|
44 |
+
|
45 |
+
result = {}
|
46 |
+
|
47 |
+
for element in root:
|
48 |
+
tag = element.tag
|
49 |
+
if tag in ['patient_name', 'date_of_birth', 'sex', 'weight', 'date_of_death']:
|
50 |
+
result[tag] = {
|
51 |
+
'reasoning': element.find('reasoning').text.strip() if element.find('reasoning') is not None else None,
|
52 |
+
**{child.tag: child.text.strip() if child.text else None
|
53 |
+
for child in element if child.tag != 'reasoning'}
|
54 |
+
}
|
55 |
+
elif tag in ['traditional_chemo', 'other_cancer_treatments', 'other_conmeds']:
|
56 |
+
if tag not in result:
|
57 |
+
result[tag] = []
|
58 |
+
reasoning = element.find('reasoning')
|
59 |
+
for item in element:
|
60 |
+
if item.tag in ['drug', 'treatment', 'medication']:
|
61 |
+
date_element = element.find('date')
|
62 |
+
result[tag].append({
|
63 |
+
'reasoning': reasoning.text.strip() if reasoning is not None else None,
|
64 |
+
'name': item.text.strip() if item.text else None,
|
65 |
+
'date': date_element.text.strip() if date_element is not None and date_element.text else None
|
66 |
+
})
|
67 |
+
elif tag in ['surgery', 'surgery_outcome', 'metastasis_at_time_of_diagnosis']:
|
68 |
+
result[tag] = {
|
69 |
+
'reasoning': element.find('reasoning').text.strip() if element.find('reasoning') is not None else None,
|
70 |
+
**{child.tag: child.text.strip() if child.text else None
|
71 |
+
for child in element if child.tag != 'reasoning'}
|
72 |
+
}
|
73 |
+
elif tag == 'compounding_pharmacy':
|
74 |
+
result[tag] = {
|
75 |
+
'reasoning': element.find('reasoning').text.strip() if element.find('reasoning') is not None else None,
|
76 |
+
'pharmacy': element.find('pharmacy').text.strip() if element.find('pharmacy') is not None else None
|
77 |
+
}
|
78 |
+
elif tag == 'adverse_effects':
|
79 |
+
if tag not in result:
|
80 |
+
result[tag] = []
|
81 |
+
effect = {
|
82 |
+
'reasoning': element.find('reasoning').text.strip() if element.find('reasoning') is not None else None
|
83 |
+
}
|
84 |
+
for child in element:
|
85 |
+
if child.tag != 'reasoning':
|
86 |
+
effect[child.tag] = child.text.strip() if child.text else None
|
87 |
+
if effect:
|
88 |
+
result[tag].append(effect)
|
89 |
+
|
90 |
+
# Convert to nested DataFrame
|
91 |
+
df_data = {}
|
92 |
+
for key, value in result.items():
|
93 |
+
if isinstance(value, dict):
|
94 |
+
for sub_key, sub_value in value.items():
|
95 |
+
df_data[(key, '1', sub_key)] = [sub_value]
|
96 |
+
elif isinstance(value, list):
|
97 |
+
for i, item in enumerate(value):
|
98 |
+
for sub_key, sub_value in item.items():
|
99 |
+
df_data[(key, f"{i+1}", sub_key)] = [sub_value]
|
100 |
+
else:
|
101 |
+
df_data[(key, '1', '')] = [value]
|
102 |
+
|
103 |
+
# Create multi-index DataFrame
|
104 |
+
df = pd.DataFrame(df_data)
|
105 |
+
df.columns = pd.MultiIndex.from_tuples(df.columns)
|
106 |
+
|
107 |
+
return df
|
108 |
+
|
109 |
+
def get_response(prompt, file_id, assistant_id):
|
110 |
+
thread = client.beta.threads.create(
|
111 |
+
messages=[
|
112 |
+
{
|
113 |
+
"role": "user",
|
114 |
+
"content": prompts.info_prompt,
|
115 |
+
"attachments": [
|
116 |
+
{"file_id": file_id, "tools": [{"type": "file_search"}]}
|
117 |
+
],
|
118 |
+
}
|
119 |
+
]
|
120 |
+
)
|
121 |
+
run = client.beta.threads.runs.create_and_poll(
|
122 |
+
thread_id=thread.id, assistant_id=assistant_id
|
123 |
+
)
|
124 |
+
messages = list(
|
125 |
+
client.beta.threads.messages.list(thread_id=thread.id, run_id=run.id)
|
126 |
+
)
|
127 |
+
assert len(messages) == 1
|
128 |
+
message_content = messages[0].content[0].text
|
129 |
+
annotations = message_content.annotations
|
130 |
+
for index, annotation in enumerate(annotations):
|
131 |
+
message_content.value = message_content.value.replace(annotation.text, f"")
|
132 |
+
return message_content.value
|
133 |
+
|
134 |
+
def process(file_content):
|
135 |
+
if not os.path.exists("cache"):
|
136 |
+
os.makedirs("cache")
|
137 |
+
file_name = f"cache/{time.time()}.pdf"
|
138 |
+
with open(file_name, "wb") as f:
|
139 |
+
f.write(file_content)
|
140 |
+
|
141 |
+
message_file = client.files.create(file=open(file_name, "rb"), purpose="assistants")
|
142 |
+
|
143 |
+
response = get_response(prompts.info_prompt, message_file.id, demo.id)
|
144 |
+
df = parse_xml_response(response)
|
145 |
+
|
146 |
+
if df.empty:
|
147 |
+
return "<p>No valid information could be extracted from the provided file.</p>"
|
148 |
+
|
149 |
+
# Transpose the DataFrame
|
150 |
+
df_transposed = df.T.reset_index()
|
151 |
+
df_transposed.columns = ['Category', 'Index', 'Field', 'Value']
|
152 |
+
df_transposed = df_transposed.sort_values(['Category', 'Index', 'Field'])
|
153 |
+
|
154 |
+
# Convert to HTML with some basic styling
|
155 |
+
html = df_transposed.to_html(index=False, classes='table table-striped table-bordered', escape=False)
|
156 |
+
|
157 |
+
# Add some custom CSS for better readability
|
158 |
+
html = f"""
|
159 |
+
<style>
|
160 |
+
.table {{
|
161 |
+
width: 100%;
|
162 |
+
max-width: 100%;
|
163 |
+
margin-bottom: 1rem;
|
164 |
+
background-color: transparent;
|
165 |
+
}}
|
166 |
+
.table td, .table th {{
|
167 |
+
padding: .75rem;
|
168 |
+
vertical-align: top;
|
169 |
+
border-top: 1px solid #dee2e6;
|
170 |
+
}}
|
171 |
+
.table thead th {{
|
172 |
+
vertical-align: bottom;
|
173 |
+
border-bottom: 2px solid #dee2e6;
|
174 |
+
}}
|
175 |
+
.table tbody + tbody {{
|
176 |
+
border-top: 2px solid #dee2e6;
|
177 |
+
}}
|
178 |
+
.table-striped tbody tr:nth-of-type(odd) {{
|
179 |
+
background-color: rgba(0,0,0,.05);
|
180 |
+
}}
|
181 |
+
</style>
|
182 |
+
{html}
|
183 |
+
"""
|
184 |
+
|
185 |
+
return html
|
186 |
+
|
187 |
+
def gradio_interface():
|
188 |
+
upload_component = gr.File(label="Upload PDF", type="binary")
|
189 |
+
output_component = gr.HTML(label="Extracted Information")
|
190 |
+
|
191 |
+
demo = gr.Interface(
|
192 |
+
fn=process,
|
193 |
+
inputs=upload_component,
|
194 |
+
outputs=output_component,
|
195 |
+
title="Clinical Note Information Extractor",
|
196 |
+
description="This tool extracts key information from clinical notes in PDF format.",
|
197 |
+
)
|
198 |
+
demo.queue()
|
199 |
+
demo.launch()
|
200 |
+
|
201 |
+
if __name__ == "__main__":
|
202 |
+
gradio_interface()
|