Quest International Journal of Medical and Health Sciences

Unmasking Guillain-Barré Syndrome resurgences in Peru and possible preventive measures

Bedanta Roy — 2024-07-01

Abstract not available.

Unveiling the enigma: The pathophysiology and risk assessment of the Marburg Virus Disease (MVD) outbreaks

Ratnadeep Saha — 2024-07-01

Introduction:

Marburg virus disease (MVD) is caused by the Marburg virus (MARV) of the Filoviridae family, causing acute hemorrhagic fever in humans. Similar to the pathogenesis of Ebola, MVD enters the body through skin cracks or mucous membranes and attacks macrophages and dendritic cells, damages cell membranes and causes cell death. In 2023, nine cases were reported in Tanzania and 17 in Equatorial Guinea. MVD remains a threat due to undetected viral spreading because of unidentified chains of transmission and potential interaction with animal reservoirs. The long presence of MVD in body fluids highlights the importance of a survivorship program.

Conclusion:

Marburgviruses are emerging due to bat distribution, environmental factors, and human behavior. The high mortality rate echoes the West African Ebola epidemic. Early diagnosis is challenging, and careful history-taking is necessary to differentiate MVD from other tropical febrile illnesses. Global agencies like WHO play a pivotal role in diagnosis and treatment.

Knowledge, attitude, and practice of artificial intelligence (AI) among medical students: A cross-sectional study from Ipoh, Perak

Kam Xoong Qin — 2024-07-01

Introduction:

Artificial intelligence (AI), replicates human intelligence, is increasingly gaining attention in higher education to address traditional educational challenges. AI offers vast potential for implementation in pathology, cardiology, radiology, and dermatology. Its potential to revolutionise the current medical practices in these areas is significant. This study aims to explore the knowledge, attitude, and practice (KAP) of AI among medical students at Quest International University in Malaysia.

Methods:

A cross-sectional descriptive study was conducted at the Faculty of Medicine, Quest International University (QIU) from January 2024 to March 2024. A structured questionnaire was distributed among the medical students of QIU, where 53 students responded to the questionnaire and participated in this research.

Results:

All students had an idea about AI, but only 54.7% were aware of the subtype classification of AI. Regarding the AI application in medical fields, radiology, and Pathology, the vast majority were unaware 73.6%, 71.7%, and 73.6% respectively. Indians have significantly good knowledge compared to other ethnicities [Chi(df) = 12.95 (4), P value = 0.005]. The majority of the students agreed upon the essentiality 48(90.6%), inclusion of AI in the medical curriculum and specialist training 44(83%), early diagnosis and disease assessment 40(75.5%), AI essentiality in radiology 36(67.9%), Pathology 38(71.7%).

Conclusion:

There is a need for training in AI which will improve the knowledge of AI and influence their attitudes towards using it in medicine. Achieving widespread and flawless AI in medicine is challenging, but a collaborative effort between education institutions and government organisations may help improve the scenario.