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Kenya

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Machine learning of blood haemoglobin and haematocrit levels via smartphone conjunctiva photography in Kenyan pregnant women: a clinical study protocol.

BMJ open
INTRODUCTION: Anaemia during pregnancy is a widespread health burden globally, especially in low- and middle-income countries, posing a serious risk to both maternal and neonatal health. The primary challenge is that anaemia is frequently undetected ...

Prediction of cardiovascular risk factors from retinal fundus photographs: Validation of a deep learning algorithm in a prospective non-interventional study in Kenya.

Diabetes, obesity & metabolism
AIM: Hypertension and diabetes mellitus (DM) are major causes of morbidity and mortality, with growing burdens in low-income countries where they are underdiagnosed and undertreated. Advances in machine learning may provide opportunities to enhance d...

Predictive modelling of linear growth faltering among pediatric patients with Diarrhea in Rural Western Kenya: an explainable machine learning approach.

BMC medical informatics and decision making
INTRODUCTION: Stunting affects one-fifth of children globally with diarrhea accounting for an estimated 13.5% of stunting. Identifying risk factors for its precursor, linear growth faltering (LGF), is critical to designing interventions. Moreover, de...

Analyzing Demographic Grocery Purchase Patterns in Kenyan Supermarkets Through Unsupervised Learning Techniques.

Inquiry : a journal of medical care organization, provision and financing
Kenya is experiencing a significant increase in the prevalence of non-communicable diseases (NCDs) such as cardiovascular diseases, hypertension, Type 2 diabetes, and certain cancers (bowel, lung, prostate, and uterine). This case is not unique to Ke...

Derivation and validation of a clinical predictive model for longer duration diarrhea among pediatric patients in Kenya using machine learning algorithms.

BMC medical informatics and decision making
BACKGROUND: Despite the adverse health outcomes associated with longer duration diarrhea (LDD), there are currently no clinical decision tools for timely identification and better management of children with increased risk. This study utilizes machin...

Machine Learning Predicts Non-Preferred and Preferred Vertebrate Hosts of Tsetse Flies (Glossina spp.) Based on Skin Volatile Emission Profiles.

Journal of chemical ecology
Tsetse fly vectors of African trypanosomosis preferentially feed on certain vertebrates largely determined by olfactory cues they emit. Previously, we established that three skin-derived ketones including 6-methyl-5-hepten-2-one, acetophenone and ger...

Machine learning to improve HIV screening using routine data in Kenya.

Journal of the International AIDS Society
INTRODUCTION: Optimal use of HIV testing resources accelerates progress towards ending HIV as a global threat. In Kenya, current testing practices yield a 2.8% positivity rate for new diagnoses reported through the national HIV electronic medical rec...

Modeling climate change impacts and predicting future vulnerability in the Mount Kenya forest ecosystem using remote sensing and machine learning.

Environmental monitoring and assessment
The Mount Kenya forest ecosystem (MKFE), a crucial biodiversity hotspot and one of Kenya's key water towers, is increasingly threatened by climate change, putting its ecological integrity and vital ecosystem services at risk. Understanding the intera...

The role of AI in reducing maternal mortality: Current impacts and future potentials: Protocol for an analytical cross-sectional study.

PloS one
BACKGROUND: Maternal and newborn mortality remains a critical public health challenge, particularly in resource-limited settings. Despite global efforts, Kenya continues to report high maternal mortality rates of over 350 deaths per 100,000 live birt...

Forecasting acute childhood malnutrition in Kenya using machine learning and diverse sets of indicators.

PloS one
OBJECTIVES: Malnutrition is a leading cause of morbidity and mortality for children under-5 globally. Low- and middle-income countries, such as Kenya, bear the greatest burden of malnutrition. The Kenyan government has been collecting clinical indica...