Uncommon Bilateral Idiopathic Facial Nerve Palsy (Bell's Palsy) in an Infant: An Atypical Age and Clinical Challenges Explored: A Case Report.

Our case study explores Bell's palsy, a rare lower motor neuron facial nerve paralysis, particularly rare in newborns. While often idiopathic, it can stem from congenital or developmental factors. Unilateral facial paralysis is more prevalent, with Bell's palsy accounting for more than 50%, while bilateral facial paralysis is exceptionally rare. We present a distinctive case of idiopathic Bell palsy in a 3.5-month-old infant, initially affecting the right side and spontaneously resolved within 30 days, followed by involvement on the left side a month later. Despite comprehensive evaluations and treatment, persistent facial weakness was observed on the left side. The patient initially responded well but faced ongoing challenges during the second attack. Our findings underscore the need for further research to improve the understanding and management of these cases.

Cerebellar abscess secondary to metastatic lung adenocarcinoma: a case report.

BACKGROUND: Cerebellar abscesses are rare, life-threatening infections often originating from bacterial sources, while metastatic brain lesions from lung adenocarcinoma are relatively common. However, the coexistence of a cerebellar abscess secondary to metastatic lung adenocarcinoma is exceedingly rare and presents unique diagnostic and management challenges. CASE PRESENTATION: We report a case of a 35 year-old Pakistani female patient with persistent headaches, nausea, and vertigo, who was found to have a large cerebellar mass with features suggestive of metastatic lung adenocarcinoma. Further investigation revealed a concomitant cerebellar abscess. Surgical excision and broad-spectrum antibiotics were initiated, resulting in a favorable outcome. CONCLUSION: This case showcases the rarity and complexity of cerebellar abscesses due to metastatic lung adenocarcinoma. Timely intervention, including surgery and targeted therapy, is crucial for successful management. Further research is needed to enhance treatment strategies.

Exploring the current and prospective role of artificial intelligence in disease diagnosis.

Artificial intelligence (AI) refers to the simulation of human intelligence processes by machines, especially computer systems, providing assistance in a variety of patient care and health systems. The aim of this review is to contribute valuable insights to the ongoing discourse on the transformative potential of AI in healthcare, providing a nuanced understanding of its current applications, future possibilities, and associated challenges. The authors conducted a literature search on the current role of AI in disease diagnosis and its possible future applications using PubMed, Google Scholar, and ResearchGate within 10 years. Our investigation revealed that AI, encompassing machine-learning and deep-learning techniques, has become integral to healthcare, facilitating immediate access to evidence-based guidelines, the latest medical literature, and tools for generating differential diagnoses. However, our research also acknowledges the limitations of current AI methodologies in disease diagnosis and explores uncertainties and obstacles associated with the complete integration of AI into clinical practice. This review has highlighted the critical significance of integrating AI into the medical healthcare framework and meticulously examined the evolutionary trajectory of healthcare-oriented AI from its inception, delving into the current state of development and projecting the extent of reliance on AI in the future. The authors have found that central to this study is the exploration of how the strategic integration of AI can accelerate the diagnostic process, heighten diagnostic accuracy, and enhance overall operational efficiency, concurrently relieving the burdens faced by healthcare practitioners.