Brain tumor analysis has undergone transformative advancements owing to the integration of deep learning, artificial intelligence (AI) and bioinformatics techniques. This comprehensive review paper explores the evolution of methodologies in diagnosing, prognosticating, and classifying brain tumors, focusing on the synergistic application of deep learning, AI and bioinformatics. Recent developments in image analysis, prognosis prediction and classification algorithms are discussed, highlighting their contributions to improving patient care and treatment outcomes. Additionally, challenges in this domain and future research directions aimed at enhancing diagnostic accuracy, prognostic reliability and classification robustness are addressed. Through the convergence of these cutting-edge technologies, researchers and clinicians can achieve enhanced understanding and management of brain tumors, ultimately leading to improved patient outcomes and advancements in neuro-oncology.

Keywords: Brain tumors, deep learning, artificial intelligence, bioinformatics, diagnosis, prognosis prediction, classification algorithms, precision medicine