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Browse files- app.py +366 -0
- requirements.txt +4 -0
app.py
ADDED
@@ -0,0 +1,366 @@
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1 |
+
import os
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2 |
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import openai
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3 |
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import langchain
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4 |
+
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langchain.debug = False
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6 |
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os.environ["TOKENIZERS_PARALLELISM"] = "false"
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os.environ["OPENAI_API_KEY"]
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def save_docs(docs):
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import shutil
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import os
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+
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output_dir = "/home/user/app/docs/"
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+
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if os.path.exists(output_dir):
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17 |
+
shutil.rmtree(output_dir)
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if not os.path.exists(output_dir):
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os.makedirs(output_dir)
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for doc in docs:
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shutil.copy(doc.name, output_dir)
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return "Successful!"
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global mdm_value
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def process_docs():
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from langchain.chat_models import ChatOpenAI
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from langchain.chains import ConversationChain
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import os
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from docx import Document
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global mdm_value
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llm = ChatOpenAI(model_name="gpt-3.5-turbo-16k")
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agent = ConversationChain(llm=llm, verbose=True)
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folder_path = "/home/user/app/docs/"
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for root, dirs, files in os.walk(folder_path):
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for file in files:
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if file.endswith(".docx") or file.endswith(".docx"):
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word_file_path = os.path.join(root, file)
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doc = Document(word_file_path)
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text = []
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50 |
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for paragraph in doc.paragraphs:
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text.append(paragraph.text)
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doc_content = "\n".join(text)
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one_word_propmt = """Classify into "MINIMAL", "LOW", "MODERATE", "HIGH". You should ALWAYS give only ONE option and NOTHING ELSE.
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ONLY return ONE option. AWAYS answer in ONLY one word. DO NOT give full sentences.
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ALWAYS give the answer in ALL UPPER CASE. DO NOT EVER give answer in any other case."""
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#####################################################
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instruction1 = """You are an expert at calculating the Risk of Complications and/or Morbidity or Mortality of the Patient Management Decisions Made at Visit (choose highest) You are provided with a detailed medical report. Classify it into "MINIMAL", "LOW", "MODERATE", and "HIGH" on the basis of the Given rules.
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MINIMAL
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Minimal risk of morbidity from additional diagnostic testing or treatment
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Examples only
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• Rest
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• Gargles
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• Elastic bandages
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68 |
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Superficial dressings
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+
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LOW
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Low risk of morbidity from additional diagnostic testing or treatment
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Examples only
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+
OTC drugs
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• Minor surgery w/no identified risk factors
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• Physical/Occtherapy
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+
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+
MODERATE
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78 |
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MODERATE risk of morbidity from additional diagnostic testing or treatment
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Examples only
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Prescription drug management
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81 |
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Decision regarding minor surgery with identified patient or procedure risk factors
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82 |
+
Decision regarding elective major surgery without identified patient or procedure risk factors
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83 |
+
Diagnosis or treatment significantly limited by social determinants of health
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84 |
+
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+
HIGH
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86 |
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HIGH risk of morbidity from additional diagnostic testing or treatment
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87 |
+
Examples only
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88 |
+
Parenteral controlled substances (DEA controlled substance given by route other than digestive tract)
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89 |
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Drug therapy requiring intensive monitoring for toxicity
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90 |
+
Decision regarding elective major surgery with identified patient or procedure risk factors
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91 |
+
Decision regarding emergency major surgery
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92 |
+
Decision regarding hospitalization or escalation of hospital level care (i.e. transfer to ICU)
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93 |
+
Decision not to resuscitate or to deescalate care because of poor prognosis
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94 |
+
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+
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96 |
+
Here is the Report """
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97 |
+
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98 |
+
instruction1 += "\n\n"
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99 |
+
instruction1 += doc_content
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100 |
+
instruction1 += "\n\n"
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101 |
+
instruction1 += "Study it and just provide your answer"
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102 |
+
response1 = agent.predict(input=instruction1)
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103 |
+
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104 |
+
instruction2 = one_word_propmt
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105 |
+
instruction2 += "\n\n"
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106 |
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instruction2 += response1
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107 |
+
response2 = agent.predict(input=instruction2) # main
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108 |
+
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109 |
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#####################################################
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110 |
+
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111 |
+
instruction3 = """Calculate Amount and/or Complexity of Data to be Reviewed & Analyzed (choose highest criteria met). You are provided with a detailed medical report. Classify it into "MINIMAL", "LOW", "MODERATE", and "HIGH" on the basis of the Given rules.
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112 |
+
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113 |
+
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114 |
+
CATEGORY 1
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115 |
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1. Review of prior external note(s) from each unique source (each unique source counted once, regardless of # of notes reviewed)
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+
2. Review of the result(s) of each unique test
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117 |
+
3. Ordering of each unique test (includes review of result, do not count in #2)
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118 |
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4. Assessment requiring an Independent historian
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119 |
+
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120 |
+
CATEGORY 2
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121 |
+
Independent interpretation of tests performed by another physician/other qualified healthcare professional (not separately reported)
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122 |
+
Do not count independent interpretation for a test billed or ordered by a colleague in the same specialty
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123 |
+
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124 |
+
CATEGORY 3
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125 |
+
Discussion of management or test interpretation- with external physician/other qualified health care professional/ appropriate source (not separately reported)
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126 |
+
Requires direct interactive exchange (not via intermediaries or notes)
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127 |
+
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128 |
+
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129 |
+
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130 |
+
MINIMAL
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131 |
+
If Minimal or No Data Reviewed
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132 |
+
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133 |
+
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134 |
+
LOW
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135 |
+
if it meets any combination of 2 from items 1-3 Or Meet item 4 (independent historian)
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136 |
+
1. Review of prior external note(s) from each unique source (each unique source counted once, regardless of # of notes reviewed)
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137 |
+
2. Review of the result(s) of each unique test
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138 |
+
3. Ordering of each unique test (includes review of result, do not count in #2)
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139 |
+
4. Assessment requiring an Independent historian
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140 |
+
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141 |
+
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142 |
+
MODERATE
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143 |
+
Meet 1 of 3 categories below
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144 |
+
Category 1: Meet any combination of 3 from items 1-4
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145 |
+
Category 2: Independent interpretation of test
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146 |
+
Category 3: Discussion management, or test interpretation (external)
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147 |
+
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148 |
+
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149 |
+
HIGH
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150 |
+
Meet 2 of 3 categories below
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151 |
+
Category 1: Meet any combination of 3 from items 1-4
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152 |
+
Category 2: Independent interpretation of test
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153 |
+
Category 3: Discussion management, or test interpretation (external)
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154 |
+
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155 |
+
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156 |
+
Here is the Report """
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157 |
+
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158 |
+
instruction3 += "\n\n"
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159 |
+
instruction3 += doc_content
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160 |
+
instruction3 += "\n\n"
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161 |
+
instruction3 += "Study it and just provide your answer"
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162 |
+
response3 = agent.predict(input=instruction3)
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163 |
+
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164 |
+
instruction4 = one_word_propmt
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165 |
+
instruction4 += "\n\n"
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166 |
+
instruction4 += response3
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167 |
+
response4 = agent.predict(input=instruction4) # main
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168 |
+
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169 |
+
#####################################################
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170 |
+
|
171 |
+
instruction5 = """You are an expert at calculating the complexity of medical problems based on Medical reports. You are provided with a detailed medical report. Classify it into "MINIMAL", "LOW", "MODERATE", and "HIGH" on the basis of the Given rules.
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172 |
+
|
173 |
+
MINIMAL
|
174 |
+
1 self- limited or minor problem
|
175 |
+
(runs a definite or prescribed course, is transient in nature, and is not likely to permanently alter health status)
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176 |
+
|
177 |
+
LOW
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178 |
+
2 or more self-limited or minor problems; or
|
179 |
+
1 stable chronic illness (chronic illness which is at treatment goal for the specific patient); or
|
180 |
+
1 acute, uncomplicated illness or injury (full recovery w/out functional impairment is expected); or
|
181 |
+
Stable, acute illness (treatment newly or recently initiated, resolution may not be complete, but condition stable); or
|
182 |
+
Acute, uncomplicated illness or injury requiring hospital inpatient or observation level care (little to no risk of mortality with treatment, but treatment required is delivered in inpt or obs setting)
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183 |
+
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184 |
+
MODERATE
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185 |
+
1 or more chronic illnesses with ex- acerbation, progression, or side effects of treatment (requires supportive care or attention to treatment for side effects); or
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186 |
+
2 or more stable chronic illnesses; or
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187 |
+
1 undiagnosed new problem with uncertain prognosis (likely to result in high risk of morbidity w/out tx); or
|
188 |
+
1 acute illness with systemic symptoms (illness that causes systemic symptoms and has high risk of morbidity without treatment); or
|
189 |
+
1 acute complicated injury (eval of body systems not part of injured organ, extensive injury, or multiple tx options are multiple and/ or associated with risk of morbidity
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190 |
+
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191 |
+
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192 |
+
HIGH
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193 |
+
• 1 or more chronic illness- es with severe exacerbation, progression, or side effects of treatment (significant risk of morbidity: may require escalation in level of care); or
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194 |
+
1 acute or chronic illness or injury that poses a threat to life or bodily
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195 |
+
function (in the near term without treatment e.g. AMI, pulmonary embolus, severe respiratory distress psychiatric illness with potential threat to self or others, peritonitis, acute renal failure)
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196 |
+
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197 |
+
Here is the Report """
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198 |
+
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199 |
+
instruction5 += "\n\n"
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200 |
+
instruction5 += doc_content
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201 |
+
instruction5 += "\n\n"
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202 |
+
instruction5 += "Study it and just provide your answer"
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203 |
+
response5 = agent.predict(input=instruction5)
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204 |
+
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205 |
+
instruction6 = one_word_propmt
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206 |
+
instruction6 += "\n\n"
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207 |
+
instruction6 += response5
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208 |
+
response6 = agent.predict(input=instruction6) # main
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209 |
+
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210 |
+
######################################################
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211 |
+
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212 |
+
inputs = [response2, response4, response6]
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213 |
+
sorted_inputs = sorted(
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214 |
+
inputs, key=lambda x: ["MINIMAL", "LOW", "MODERATE", "HIGH"].index(x)
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215 |
+
)
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216 |
+
mdm_value = sorted_inputs[1]
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217 |
+
print(mdm_value)
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218 |
+
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219 |
+
return (
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220 |
+
"Successful!",
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221 |
+
response1,
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222 |
+
response2,
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223 |
+
response3,
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224 |
+
response4,
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225 |
+
response5,
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226 |
+
response6,
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227 |
+
)
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228 |
+
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229 |
+
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230 |
+
def get_code1(input):
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231 |
+
global mdm_value
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232 |
+
mdm_value = mdm_value
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233 |
+
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234 |
+
if input == "NEW" and mdm_value == "MINIMAL":
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235 |
+
hcpcs_code = "99202"
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236 |
+
elif input == "NEW" and mdm_value == "LOW":
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237 |
+
hcpcs_code = "99203"
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238 |
+
elif input == "NEW" and mdm_value == "MODERATE":
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239 |
+
hcpcs_code = "99204"
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240 |
+
elif input == "NEW" and mdm_value == "HIGH":
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241 |
+
hcpcs_code = "99205"
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242 |
+
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243 |
+
elif input == "ESTABLISHED" and mdm_value == "MINIMAL":
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244 |
+
hcpcs_code = "99212"
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245 |
+
elif input == "ESTABLISHED" and mdm_value == "LOW":
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246 |
+
hcpcs_code = "99213"
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247 |
+
elif input == "ESTABLISHED" and mdm_value == "MODERATE":
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248 |
+
hcpcs_code = "99214"
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249 |
+
elif input == "ESTABLISHED" and mdm_value == "HIGH":
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250 |
+
hcpcs_code = "99215"
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251 |
+
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252 |
+
return hcpcs_code
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253 |
+
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254 |
+
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255 |
+
def get_code2(input):
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256 |
+
if input == "20 min":
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257 |
+
hcpcs_code = "99242"
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258 |
+
elif input == "30 min":
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259 |
+
hcpcs_code = "99243"
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260 |
+
elif input == "40 min":
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261 |
+
hcpcs_code = "99244"
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262 |
+
elif input == "55 min":
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263 |
+
hcpcs_code = "99245"
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264 |
+
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265 |
+
return hcpcs_code
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266 |
+
|
267 |
+
|
268 |
+
import gradio as gr
|
269 |
+
|
270 |
+
css = """
|
271 |
+
.col{
|
272 |
+
max-width: 70%;
|
273 |
+
margin: 0 auto;
|
274 |
+
display: flex;
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275 |
+
flex-direction: column;
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276 |
+
justify-content: center;
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277 |
+
align-items: center;
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278 |
+
}
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279 |
+
"""
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280 |
+
|
281 |
+
with gr.Blocks(css=css) as demo:
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282 |
+
gr.Markdown("## <center>Medical assistant bot</center>")
|
283 |
+
|
284 |
+
with gr.Tab("Get help with medical documents"):
|
285 |
+
with gr.Column(elem_classes="col"):
|
286 |
+
with gr.Tab("Upload and Process Document"):
|
287 |
+
with gr.Row():
|
288 |
+
with gr.Column():
|
289 |
+
docs_upload_input = gr.Files(label="Upload File")
|
290 |
+
docs_upload_button = gr.Button("Upload")
|
291 |
+
docs_upload_output = gr.Textbox(label="Output")
|
292 |
+
|
293 |
+
docs_process_button = gr.Button("Process")
|
294 |
+
docs_process_output = gr.Textbox(label="Output")
|
295 |
+
|
296 |
+
gr.ClearButton(
|
297 |
+
[docs_upload_input, docs_upload_output, docs_process_output]
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298 |
+
)
|
299 |
+
|
300 |
+
with gr.Column():
|
301 |
+
ai_output1 = gr.Textbox(label="Output 1")
|
302 |
+
ai_output2 = gr.Textbox(label="Output 2")
|
303 |
+
ai_output3 = gr.Textbox(label="Output 3")
|
304 |
+
ai_output4 = gr.Textbox(label="Output 4")
|
305 |
+
ai_output5 = gr.Textbox(label="Output 5")
|
306 |
+
ai_output6 = gr.Textbox(label="Output 6")
|
307 |
+
|
308 |
+
gr.ClearButton(
|
309 |
+
[
|
310 |
+
ai_output1,
|
311 |
+
ai_output2,
|
312 |
+
ai_output3,
|
313 |
+
ai_output4,
|
314 |
+
ai_output5,
|
315 |
+
ai_output6,
|
316 |
+
]
|
317 |
+
)
|
318 |
+
|
319 |
+
with gr.Tab("Get HCPCS Code (Primary Care Exception)"):
|
320 |
+
with gr.Column():
|
321 |
+
code_type_input1 = gr.Dropdown(choices=["NEW", "ESTABLISHED"])
|
322 |
+
code_type_button1 = gr.Button("Submit")
|
323 |
+
code_type_output1 = gr.Textbox(label="Output")
|
324 |
+
|
325 |
+
gr.ClearButton([code_type_input1, code_type_output1])
|
326 |
+
|
327 |
+
with gr.Tab("Get HCPCS Code (CONSULTATION)"):
|
328 |
+
with gr.Column():
|
329 |
+
code_type_input2 = gr.Dropdown(
|
330 |
+
choices=["20 min", "30 min", "40 min", "55 min"]
|
331 |
+
)
|
332 |
+
code_type_button2 = gr.Button("Submit")
|
333 |
+
code_type_output2 = gr.Textbox(label="Output")
|
334 |
+
|
335 |
+
gr.ClearButton([code_type_input2, code_type_output2])
|
336 |
+
|
337 |
+
#########################################################################################################
|
338 |
+
|
339 |
+
docs_upload_button.click(
|
340 |
+
save_docs, inputs=docs_upload_input, outputs=docs_upload_output
|
341 |
+
)
|
342 |
+
docs_process_button.click(
|
343 |
+
process_docs,
|
344 |
+
inputs=None,
|
345 |
+
outputs=[
|
346 |
+
docs_process_output,
|
347 |
+
ai_output1,
|
348 |
+
ai_output2,
|
349 |
+
ai_output3,
|
350 |
+
ai_output4,
|
351 |
+
ai_output5,
|
352 |
+
ai_output6,
|
353 |
+
],
|
354 |
+
)
|
355 |
+
|
356 |
+
code_type_button1.click(
|
357 |
+
get_code1, inputs=code_type_input1, outputs=code_type_output1
|
358 |
+
)
|
359 |
+
code_type_button2.click(
|
360 |
+
get_code2, inputs=code_type_input2, outputs=code_type_output2
|
361 |
+
)
|
362 |
+
|
363 |
+
#########################################################################################################
|
364 |
+
|
365 |
+
demo.queue()
|
366 |
+
demo.launch(debug=True, share=True)
|
requirements.txt
ADDED
@@ -0,0 +1,4 @@
|
|
|
|
|
|
|
|
|
|
|
1 |
+
langchain
|
2 |
+
python-docx
|
3 |
+
gradio
|
4 |
+
openai
|