Create app.py

app.py

@@ -0,0 +1,138 @@
+import pickle
+
+import gradio as gr
+import numpy as np
+import pandas as pd
+
+
+class ModelPredictor:
+    def __init__(self, model_path, model_filenames):
+        self.model_path = model_path
+        self.model_filenames = model_filenames
+        self.models = self.load_models()
+        self.prediction_map = {
+            'YOWRDISC': ["Did not feel discouraged about life every day", "Felt discouraged about life every day"],
+            'YO_MDEA3': ["Does not have changes in appetite or weight", "Has changes in appetite or weight"],
+            'YOPB2WK': ["Did not feel this way for 2 weeks or more with other problems during the past 12 months", "Felt this way for 2 weeks or more with other problems during the past 12 months"],
+            'YOWRDCSN': ["Able to make decisions when problems were worst", "Unable to make decisions when problems were worst"],
+            'YODPDISC': ["Did not feel discouraged about life when sad/empty/depressed", "Felt discouraged about life when sad/empty/depressed"],
+            'YOWRELES': ["Did not eat less than usual every day when problems were worst", "Ate less than usual every day when problems were worst"],
+            'YORX12MO': ["Not currently receiving treatment/counseling for mood", "Currently receiving treatment/counseling for mood"],
+            'YODPLSIN': ["Did not lose interest in things when sad/empty/depressed", "Lost interest in things when sad/empty/depressed"],
+            'YODSCEV': ["Never had a period of time where felt discouraged or hopeless", "Ever had a period of time where felt discouraged or hopeless"],
+            'YO_MDEA8': ["Ability to concentrate or make decisions", "Inability to concentrate or make decisions"],
+            'YOWRHRS': ["Time that most severe/frequent mood lasted less than 1 hour", "Time that most severe/frequent mood lasted at least 1 hour but no more than 3 hours", "Time that most severe/frequent mood lasted at least 3 hours but no more than 5 hours"],
+            'YOWRIMP': ["Mood so severe couldn't do daily activities not very often", "Mood so severe couldn't do daily activities sometimes", "Mood so severe couldn't do daily activities often"],
+            'YO_MDEA2': ["Did not lose interest or pleasure in most things", "Lost interest or pleasure in most things"],
+            'YODPPROB': ["Never had other problems during 2 weeks or longer", "Ever had other problems during 2 weeks or longer"],
+            'YOWRPROB': ["No particular time that is the worst one ever", "One particular time that is the worst one ever"],
+            'YOLOSEV': ["Never had a period of time lost interest in enjoyable things", "Ever had a period of time lost interest in enjoyable things"],
+            'YO_MDEA5': ["Others did not notice that was restless or lethargic", "Others noticed that was restless or lethargic"],
+            'YODSMMDE': ["Has less than 5 symptoms", "Has 5 or more symptoms"],
+            'YODPR2WK': ["No time when feelings lasted every day for 2 weeks or longer", "Time when feelings lasted every day for 2 weeks or longer"]
+        }
+
+    def load_models(self):
+        models = []
+        for filename in self.model_filenames:
+            filepath = self.model_path + filename
+            with open(filepath, 'rb') as file:
+                model = pickle.load(file)
+            models.append(model)
+        return models
+
+    def make_predictions(self, user_input):
+        predictions = []
+        for model in self.models:
+            pred = model.predict(user_input)
+            pred = np.array(pred).flatten()
+            predictions.append(pred)
+        return predictions
+
+    def get_majority_vote(self, predictions):
+        combined_predictions = np.concatenate(predictions)
+        majority_vote = np.bincount(combined_predictions).argmax()
+        return majority_vote
+
+    def evaluate_severity(self, majority_vote_count):
+        if majority_vote_count > 10:
+            return "Mental health severity: Severe"
+        elif majority_vote_count > 7:
+            return "Mental health severity: Moderate"
+        elif majority_vote_count > 4:
+            return "Mental health severity: Low"
+        else:
+            return "Mental health severity: Very Low"
+
+model_filenames = [
+    "YOWRDISC.pkl", "YO_MDEA3.pkl", "YOPB2WK.pkl", "YOWRDCSN.pkl", "YODPDISC.pkl", 
+    "YOWRELES.pkl", "YORX12MO.pkl", "YODPLSIN.pkl", "YOWRIMP.pkl", "YODPPROB.pkl", 
+    "YOWRPROB.pkl", "YOLOSEV.pkl", "YO_MDEA5.pkl", "YODSMMDE.pkl", "YODPR2WK.pkl"
+]
+model_path = "models/"
+predictor = ModelPredictor(model_path, model_filenames)
+
+def predict(user_inputs):
+    user_input_data = {key: [int(value)] for key, value in user_inputs.items()}
+    user_input = pd.DataFrame(user_input_data)
+    predictions = predictor.make_predictions(user_input)
+    majority_vote = predictor.get_majority_vote(predictions)
+    majority_vote_count = sum([1 for pred in np.concatenate(predictions) if pred == 1])
+    severity = predictor.evaluate_severity(majority_vote_count)
+
+    results = []
+    for i, pred in enumerate(predictions):
+        model_name = model_filenames[i].split('.')[0]
+        pred_value = pred[0]
+        if model_name in predictor.prediction_map:
+            if pred_value < len(predictor.prediction_map[model_name]):
+                results.append(f"Prediction from model {model_name}: {predictor.prediction_map[model_name][pred_value]}")
+            else:
+                results.append(f"Prediction from model {model_name}: Unknown prediction value {pred_value}")
+        else:
+            results.append(f"Prediction from model {model_name}: Unknown model")
+
+    return results, severity
+
+inputs = [
+    gr.inputs.Dropdown(["1", "0"], label="YNURSMDE (1 = Yes, 0 = No)"),
+    gr.inputs.Dropdown(["1", "2"], label="YMDEYR (1 = Yes, 2 = No)"),
+    gr.inputs.Dropdown(["1", "0"], label="YSOCMDE (1 = Yes, 0 = No)"),
+    gr.inputs.Dropdown(["1", "2"], label="YUCOSUITHK (1 = Yes, 2 = No)"),
+    gr.inputs.Dropdown(["1", "2", "3", "4"], label="YMDESUD5ANYO (1 = SUD only, no MDE, 2 = MDE only, no SUD, 3 = SUD and MDE, 4 = Neither SUD or MDE)"),
+    gr.inputs.Dropdown(["1", "0"], label="YMSUD5YANY (1 = Yes, 0 = No)"),
+    gr.inputs.Dropdown(["1", "2", "3", "4"], label="YUSUITHK (1 = Yes, 2 = No, 3 = I'm not sure, 4 = I don't want to answer)"),
+    gr.inputs.Dropdown(["1", "0"], label="YMDETXRX (1 = Yes, 0 = No)"),
+    gr.inputs.Dropdown(["1", "2", "3", "4"], label="YUSUITHKYR (1 = Yes, 2 = No, 3 = I'm not sure, 4 = I don't want to answer)"),
+    gr.inputs.Dropdown(["1", "0"], label="YMDERSUD5ANY (1 = Yes, 0 = No)"),
+    gr.inputs.Dropdown(["1", "2", "3", "4"], label="YUSUIPLNYR (1 = Yes, 2 = No, 3 = I'm not sure, 4 = I don't want to answer)"),
+    gr.inputs.Dropdown(["1", "0"], label="YCOUNMDE (1 = Yes, 0 = No)"),
+    gr.inputs.Dropdown(["1", "0"], label="YPSY1MDE (1 = Yes, 0 = No)"),
+    gr.inputs.Dropdown(["1", "0"], label="YHLTMDE (1 = Yes, 0 = No)"),
+    gr.inputs.Dropdown(["1", "0"], label="YDOCMDE (1 = Yes, 0 = No)"),
+    gr.inputs.Dropdown(["1", "0"], label="YPSY2MDE (1 = Yes, 0 = No)"),
+    gr.inputs.Dropdown(["1", "0"], label="YMDEHARX (1 = Yes, 0 = No)"),
+    gr.inputs.Dropdown(["1", "2", "3"], label="LVLDIFMEM2 (1 = No Difficulty, 2 = Some difficulty, 3 = A lot of difficulty or cannot do at all)"),
+    gr.inputs.Dropdown(["1", "2"], label="MDEIMPY (1 = Yes, 2 = No)"),
+    gr.inputs.Dropdown(["1", "0"], label="YMDEHPO (1 = Yes, 0 = No)"),
+    gr.inputs.Dropdown(["1", "2", "3", "4", "5"], label="CONEGMH (1 = Not at all, 2 = A little, 3 = Some, 4 = Quite a bit, 5 = A lot)"),
+    gr.inputs.Dropdown(["1", "2", "3"], label="COCLNEGMH (1 = Not at all, 2 = A little or some, 3 = Quite a bit or a lot)"),
+    gr.inputs.Dropdown(["1", "0"], label="YMIMS5YANY (1 = Yes, 0 = No)"),
+    gr.inputs.Dropdown(["1", "0"], label="YMDEIMAD5YR (1 = Yes, 0 = No)"),
+    gr.inputs.Dropdown(["1", "0"], label="YMIUD5YANY (1 = Yes, 0 = No)"),
+    gr.inputs.Dropdown(["1", "2"], label="YUCOSUIPLN (1 = Yes, 2 = No)"),
+    gr.inputs.Dropdown(["1", "0"], label="YMDEHPRX (1 = Yes, 0 = No)"),
+    gr.inputs.Dropdown(["1", "0"], label="YMIMI5YANY (1 = Yes, 0 = No)"),
+    gr.inputs.Dropdown(["1", "2", "3", "4"], label="YUSUIPLN (1 = Yes, 2 = No, 3 = I'm not sure, 4 = I don't want to answer)"),
+    gr.inputs.Dropdown(["1", "0"], label="YTXMDEYR (1 = Yes, 0 = No)"),
+    gr.inputs.Dropdown(["1", "0"], label="YMDEAUD5YR (1 = Yes, 0 = No)"),
+    gr.inputs.Dropdown(["1", "0"], label="YRXMDEYR (1 = Yes, 0 = No)"),
+    gr.inputs.Dropdown(["1", "2"], label="YMDELT (1 = Yes, 2 = No)")
+]
+
+outputs = [
+    gr.outputs.Textbox(label="Prediction Results"),
+    gr.outputs.Textbox(label="Mental Health Severity")
+]
+
+gr.Interface(fn=predict, inputs=inputs, outputs=outputs, title="Adolescent Mental Health Prediction").launch()