The goal of this clinical trial is to learn if an Arabic-language mobile application that uses artificial intelligence (AI) can help women with breast cancer during chemotherapy. The app is designed to give personalized support by reminding participants about their medications, teaching them how to manage treatment side effects, and alerting their healthcare team about serious symptoms.

The main questions this study aims to answer are:

1. Does the AI-based mobile app provide accurate and safe recommendations for the patients?
2. Does using the AI-based mobile app help lower treatment-related symptoms and side effects compared to usual care?
3. Does the app help participants take their medications more regularly?
4. Does it increase participants' understanding and satisfaction with the information they receive about their treatment?

Researchers will compare two groups:

Group 1: Participants who use the AI-based mobile app plus usual oncology care. Group 2: Participants who receive usual care only.

Participants will:

1. Use the mobile app daily for 12 weeks while receiving chemotherapy.
2. Complete short questionnaires about symptoms, medication use, and quality of life at the start and end of the study.
3. Report any problems or feedback about using the app. The AI app is for support and education only. It does not make treatment decisions. All information from the app will be reviewed by oncologists and pharmacists to ensure participant safety.

Despite advances in oncology care, breast cancer patients in Iraq face significant challenges regarding medication adherence and symptom management during the inter-cycle chemotherapy periods. This randomized controlled trial aims to bridge this gap by evaluating the efficacy, safety, and feasibility of a specialized, Arabic-language Artificial Intelligence (AI) mobile application.

Current standard care in the local setting often relies on episodic clinic visits, leaving patients without real-time support for side effects experienced at home. This study hypothesizes that a continuous, AI-driven digital intervention can reduce symptom burden and improve adherence to chemotherapy and supportive care medications (e.g., antiemetics) compared to standard care alone. The application utilizes Natural Language Processing (NLP) to provide conversational support tailored specifically to the cultural and linguistic context of Iraqi patients.

The intervention integrates a "Human-in-the-loop" safety model to ensure clinical accuracy. The AI algorithms are trained on clinical practice guidelines adapted for the local formulary.

Symptom Triage Logic: The app utilizes an algorithm based on the CTCAE grading system. Low-grade symptoms trigger self-care advice (e.g., hydration, dietary changes), while high-grade symptoms trigger immediate alerts to the patient to seek care and a notification to the study investigators.

Adherence Algorithms: Unlike static alarms, the notification system adapts to the specific chemotherapy cycle (e.g., AC or Taxane-based regimens) to remind patients of specific supportive medications required on specific days.

Control Group Specification (Standard of Care) Participants randomized to the control arm will receive the institutional standard of care. This includes routine oncologist consultations, standard written or verbal discharge instructions regarding chemotherapy side effects, and pharmacy dispensing counseling. They will not have access to the interactive AI features but will undergo the same schedule of outcome assessments to ensure rigorous comparison.

This study represents the first empirical effort to integrate AI-driven digital health tools into the public oncology sector in Iraq. It aims to validate whether automated, algorithmic triage is a feasible addition to the healthcare infrastructure in low-resource settings.

Inclusion Criteria:

• Confirmed diagnosis of breast cancer stages I, II, or III.
• Patients must be currently scheduled to initiate their first-ever cycle of chemotherapy.
• Age 18 years or older.
• Ability to understand and provide informed consent.
• Possession of a smartphone (Android or iOS) and functional digital literacy, defined as the ability to independently navigate mobile applications, read on-screen text in Arabic, and input daily health data. (for the intervention group).
• Willingness to comply with study procedures and follow-up schedules.
• Ability to communicate in Arabic, as the mobile application and chatbot will be developed in Arabic.

Exclusion Criteria:

• Patients with Stage IV (Metastatic) breast cancer.
• Patients receiving concurrent hormonal therapy during the chemotherapy phase, to isolate chemotherapy-induced adverse events.

Patients with cognitive impairment or severe psychiatric disorders that would preclude effective interaction with the mobile application or questionnaire completion.

• Patients receiving palliative care where symptom management is the sole focus and active chemotherapy is not being administered with curative or life prolonging intent.
• Patients participating in other interventional clinical trials that might confound the outcomes of this study.
• Patients with severe comorbidities that could significantly impact their ability to participate or bias outcome measures.

Deidentified individual participant data (IPD) that underlie the results reported in published articles will be made available to qualified academic researchers upon reasonable request. Data sharing will occur after publication of the main results and subject to approval by the Research Ethics Committee, College of Pharmacy, University of Baghdad. Data will include coded variables without any identifiers to ensure participant confidentiality.

Deidentified individual participant data and related documents will be available beginning 6 months after publication of the main study results and for up to 3 years thereafter. Requests beyond this period will be considered on a case-by-case basis depending on data availability and ethical approval.

Access to the deidentified data will be granted to qualified investigators for non-commercial academic research. Requests must include a clear research proposal and data-use agreement ensuring data protection. Data will be shared electronically through secure university-approved transfer methods after approval by the principal investigator and the Research Ethics Committee, College of Pharmacy, University of Baghdad.