## 3 Results and Discussion
The healthcare worker is shown a user-friendly dashboard in Figure 10 following a successful system login. The dashboard allows the healthcare professional to register new patients and view the list of registered patients. The healthcare professional can either automatically navigate to the patient's dashboard (Figure 11) following a successful patient registration or search for and click on the patient's name from the patient list. The patient's dashboard allows them to view their past medical history as well as take and examine their history (Figure 12). As seen in Figure 13, the mobile app provides provisional diagnoses following a successful history taking and examination. It lists all probable diseases the patient may have along with a LIME chart and a ChatGPT explanation of the diagnoses. \begin{table}
\begin{tabular}{l} \hline \hline Explain the LIME results below (disease or diseases and significant symptoms) to a physician with not more than 300 words: \\ Predictions [”lynlynbot Fever Likely”, “HIV/AIDS Likely”, “Uninary Tract Infection Likely”, “Respiratory Tract Infection Likely”, \\ “Tuberculosis Likely”] \\ LIME Explanation; \\ BITTER TASTE IN MOUTH \(<=1.00\); \(-0.16758919765052108\) \\ Painful Orientation \(>1.00\); \(-0.06605868111597245\) \\ Suprupubic\_Pain \(>1.00\); \(-0.06550467141471979\) \\ Difficulty Breathing \(<=1.00\); \(0.060176178705925383\) \\ Wheening \(<=1.00\); \(0.05806462921972053\) \\ Headache \(<=1.00\); \(-0.058052647312462451\) \\ CHIILS AND RICGORS \(<1.00\); \(-0.05630271637802242\) \\ CHEST INDRAW \(<1.00\); \(0.0400705887842\) \\ Generalized Body Pain \(>3.00\); \(0.039799933610306\) \\ 1.00 \(<\) CATARRH \(<=2.00\); \(0.03816070620416529\) \\ Urinary. Frequency \(>1.00\); \(-0.03770207676285268\) \\ ABDOMINAL PAAN \(>3.00\); \(-0.03930297087385111155\) \\ 2.00 \(<\) Fever \(<=3.00\); \(0.039299053123995245\) \\ 1.00 \(<\) Muscle and Body Pain \(<=3.00\); \(0.03295097711760973\) \\ HCGPEver \(>3.00\); \(0.032950800019691147\) \\ BLODODV URINE \(>1.00\); \(-0.029958413923477\) \\ Cough (Initial Dry) \(<=1.00\); \(0.026364166193042264\) \\ CHEST PAN \(<=1.00\); \(0.025488917641192\) \\ Store_Thrust \(>1.00\); \(-0.0210420483028056374\) \\ Lymph Node Swelling \(>1.00\); \(-0.0202552321969518\) \\ Vomiting \(>2.00\); \(0.010957251353418118\) \\ Leathers \(>2.00\); \(-0.0173741860508137\) \\ Mouth Dicer \(>1.00\); \(-0.01586144250446513\) \\ Fatigue \(>3.00\); \(-0.0151282956507896\) \\ Generalized Rash \(<=1.00\); \(0.014081682731125898\) \\ Fould Health \(<=1.00\); \(0.012069364391423\) \\ 1.00 \(<\) LWEDFever \(<=3.00\); \(0.0121458735432654306\) \\ CONSTITATION \(<=1.00\); \(-0.012145436356090885\)This tool could aid healthcare workers in diagnosing febrile diseases while addressing the critical need for transparency in AI-driven healthcare solutions. With a good balance between interpretability and diagnostic performance, Random Forest was reliable and easily interpreted, showing a strong performance in diagnosing most of the febrile diseases, and its moderate complexity makes it easier to integrate into mobile apps for real-time diagnoses. RF's interpretability through LIME makes it easier for healthcare professionals to understand the diagnoses and validate the system, crucial for real-world application in healthcare settings. The ChatGPT model explanation is suitable for use in our system because of its context-based explanations of complex results. ChatGPT, as a large language model, can generate relevant and contextually appropriate diagnostic information based on patient symptoms. In this case, the diagnoses for diseases like typhoid fever, HIV/AIDS, urinary tract infection, respiratory tract infection, and tuberculosis are aligned with known medical presentations. The combination of symptom-specific input and advanced language processing allows the ChatGPT model to interpret complex medical data, making it valuable for diagnosis in resource-scar settings. Figure 10: Healthcare dashboard. Figure 11: Patient dashboard. Figure 12: History taking and examination.