Host cytokine genetic polymorphisms in a selected population of persons living with hepatitis B virus infection in the central region of Ghana.

Background: Hepatitis B virus (HBV) infection is a public health concern in resource limited settings like Ghana. Over the past decades, it is noted that the natural course of HBV in persons infected are taking a worse turn leading to liver cirrhosis and cancer. The outcome of HBV infection is influenced by viral and host factors including genetics.

Therapeutic efficacy of generic artemether-lumefantrine in the treatment of uncomplicated malaria in Ghana: assessing anti-malarial efficacy amidst pharmacogenetic variations.

Background: Despite efforts made to reduce morbidity and mortality associated with malaria, especially in sub-Saharan Africa, malaria continues to be a public health concern that requires innovative efforts to reach the WHO-set zero malaria agenda. Among the innovations is the use of artemisinin-based combination therapy (ACT) that is effective against Plasmodium falciparum. Generic artemether-lumefantrine (AL) is used to treat uncomplicated malaria after appropriate diagnosis.

Apolipoprotein E genetic variation, atherogenic index and cardiovascular disease risk assessment in an African population: An analysis of HIV and malaria patients in Ghana.

Background: Apolipoprotein E is involved in lipid transport and clearance of lipoprotein through low-density lipoprotein receptors (LDLR). ApoE variation has been linked to cardiovascular disease (CVD) risk. There are 3 isoforms of ApoE which originate from two non-synonymous single nucleotide polymorphisms denoted as ε2, ε3 and ε4.

Implementing Artificial Intelligence and Digital Health in Resource-Limited Settings? Top 10 Lessons We Learned in Congenital Heart Defects and Cardiology.

Artificial intelligence (AI) is one of the key drivers of digital health. Digital health and AI applications in medicine and biology are emerging worldwide, not only in resource-rich but also resource-limited regions. AI predates to the mid-20th century, but the current wave of AI builds in part on machine learning (ML), big data, and algorithms that can learn from massive amounts of online user data from patients or healthy persons.