Spaces:
Sleeping
Sleeping
File size: 8,222 Bytes
d18fef3 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 |
"""
CDSS Rule Editor Component
"""
import gradio as gr
import pandas as pd
import json
import ast
def parse_rules():
with open("rules.py", "r") as f:
tree = ast.parse(f.read())
rules = {"Mother": [], "Neonate": [], "Gyn": []}
for node in ast.walk(tree):
if isinstance(node, ast.FunctionDef) and node.name == "rule_based_cdss":
for body_item in node.body:
if (
isinstance(body_item, ast.If)
and isinstance(body_item.test, ast.Compare)
and isinstance(body_item.test.left, ast.Attribute)
and isinstance(body_item.test.left.value, ast.Name)
and body_item.test.left.value.id == "state"
and body_item.test.left.attr == "patient_type"
and isinstance(body_item.test.ops[0], ast.Eq)
and isinstance(body_item.test.comparators[0], ast.Constant)
):
patient_type = body_item.test.comparators[0].value
if patient_type in rules:
for rule_node in body_item.body:
if isinstance(rule_node, ast.If):
conditions = ast.unparse(rule_node.test)
alert = ""
for item in rule_node.body:
if (
isinstance(item, ast.Expr)
and isinstance(item.value, ast.Call)
and hasattr(item.value.func, "value")
and hasattr(item.value.func.value, "id")
and item.value.func.value.id == "alerts"
and item.value.func.attr == "append"
and isinstance(item.value.args[0], ast.Constant)
):
alert = item.value.args[0].value
rules[patient_type].append(
{"conditions": conditions, "alert": alert}
)
return rules
def rules_to_dataframes(rules):
dataframes = {}
for patient_type, rules_list in rules.items():
data = {"Conditions": [], "Alert": []}
for rule in rules_list:
data["Conditions"].append(rule["conditions"])
data["Alert"].append(rule["alert"])
df = pd.DataFrame(data)
dataframes[patient_type] = df
return dataframes
def dataframes_to_rules(dfs):
rules = {"Mother": [], "Neonate": [], "Gyn": []}
for patient_type, df in dfs.items():
if df is not None:
for index, row in df.iterrows():
if row["Conditions"] and row["Alert"]:
rules[patient_type].append(
{"conditions": row["Conditions"], "alert": row["Alert"]}
)
return rules
def add_row(df):
if df is None:
df = pd.DataFrame(columns=["Conditions", "Alert"])
df.loc[len(df)] = ["", ""]
return df
def save_rules(df_mother, df_neonate, df_gyn):
dfs = {"Mother": df_mother, "Neonate": df_neonate, "Gyn": df_gyn}
for patient_type, df in dfs.items():
if not isinstance(df, pd.DataFrame):
dfs[patient_type] = pd.DataFrame(df, columns=["Conditions", "Alert"])
rules = dataframes_to_rules(dfs)
with open("rules.py", "r") as f:
tree = ast.parse(f.read())
for node in ast.walk(tree):
if isinstance(node, ast.FunctionDef) and node.name == "rule_based_cdss":
node.body = []
node.body.append(ast.parse("v = state.vitals").body[0])
node.body.append(ast.parse("labs = state.labs").body[0])
node.body.append(ast.parse("alerts = []").body[0])
for patient_type, rule_list in rules.items():
if_patient_type_body = []
for rule in rule_list:
conditions = (
rule["conditions"].replace("\r", " ").replace("\n", " ")
)
if_rule_str = f"if {conditions}:\n alerts.append({json.dumps(rule['alert'])})"
if_rule = ast.parse(if_rule_str).body[0]
if_patient_type_body.append(if_rule)
if if_patient_type_body:
if_patient_type = ast.If(
test=ast.Compare(
left=ast.Attribute(
value=ast.Name(id="state", ctx=ast.Load()),
attr="patient_type",
ctx=ast.Load(),
),
ops=[ast.Eq()],
comparators=[ast.Constant(value=patient_type)],
),
body=if_patient_type_body,
orelse=[],
)
node.body.append(if_patient_type)
node.body.append(
ast.parse(
'if not alerts:\\n return "Tidak ada alert prioritas tinggi. Lanjutkan pemantauan dan dokumentasi."'
).body[0]
)
node.body.append(
ast.parse(
'return "\\n- ".join(["ALERT:"] + alerts)', mode="single"
).body[0]
)
new_code = ast.unparse(tree)
with open("rules.py", "w") as f:
f.write(new_code)
return "Rules saved successfully."
def editor_ui():
with gr.TabItem("Rule Editor"):
with gr.Tabs():
with gr.TabItem("Edit Rules"):
gr.Markdown("## CDSS Rule Editor")
initial_rules = parse_rules()
initial_dfs = rules_to_dataframes(initial_rules)
with gr.Tabs():
with gr.Tab("Mother"):
df_mother = gr.DataFrame(
value=initial_dfs["Mother"],
headers=["Conditions", "Alert"],
interactive=True,
row_count=(len(initial_dfs["Mother"]) + 1, "dynamic"),
type="pandas",
)
add_mother_btn = gr.Button("➕ Add Mother Rule")
add_mother_btn.click(
add_row, inputs=df_mother, outputs=df_mother
)
with gr.Tab("Neonate"):
df_neonate = gr.DataFrame(
value=initial_dfs["Neonate"],
headers=["Conditions", "Alert"],
interactive=True,
row_count=(len(initial_dfs["Neonate"]) + 1, "dynamic"),
type="pandas",
)
add_neonate_btn = gr.Button("➕ Add Neonate Rule")
add_neonate_btn.click(
add_row, inputs=df_neonate, outputs=df_neonate
)
with gr.Tab("Gyn"):
df_gyn = gr.DataFrame(
value=initial_dfs["Gyn"],
headers=["Conditions", "Alert"],
interactive=True,
row_count=(len(initial_dfs["Gyn"]) + 1, "dynamic"),
type="pandas",
)
add_gyn_btn = gr.Button("➕ Add Gyn Rule")
add_gyn_btn.click(add_row, inputs=df_gyn, outputs=df_gyn)
save_button = gr.Button("💾 Save Rules")
status_textbox = gr.Textbox(label="Status", interactive=False)
save_button.click(
save_rules,
inputs=[df_mother, df_neonate, df_gyn],
outputs=status_textbox,
)
return df_mother, df_neonate, df_gyn, save_button, status_textbox
|