Developing Artificial Intelligence-based Algorism to Predict Side Effects and Symptoms From Chemotherapy

Developing Artificial Intelligence-based Algorism Based on Life-log Data Acquired From Wearable Device for the Prediction of Chemotherapy-induced Side Effects and Symptom

In this study, the investigators obtain wearable disease based biomarkers from patients diagnosed with cancer and undergoing chemotherapy, and simultaneously measure patient self-reported adverse events through an app to evaluate chemotherapy completion rates, emergency room visits, and frequency of CTCAE adverse events.

The investigators will develop an artificial intelligence-based algorism that can predict patients' side effects based on biomarkers alone.

In this study, patients diagnosed with lung, head and neck, and esophageal cancers and undergoing chemotherapy will be measured for self-reported side effects using a wearable device to collect biomarkers through an app, and the association between patient quality of life and side effects and biomarkers obtained from the wearable device will be analyzed. On the other hand, blood (EDTA 3cc) for pharmacogenomics testing will be tested once at any point during the study period as an indicator associated with side effects after chemotherapy.

Inclusion Criteria:

• 20 years of age or older

• Must have diagnosed with lung, head and neck, or esophageal cancer,

  1. scheduled to receive their first treatment in preoperative or postoperative chemotherapy.
  2. scheduled for systemic chemotherapy due to recurrence or metastasis.

• Eastern Cooperative Oncology (ECOG) performance status of 0 to 2.

• Patients who have access to a smartphone and can use the mobile app on their own.

• Understand the purpose of the study and agree to participate in the study.

Exclusion Criteria:

• Patients who, in the judgment of the researcher, have difficulty using the application.
• Patients who are judged by the medical staff to be unable to participate in the study.