AIMC Topic: Humans

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Development and validation of artificial intelligence models for automated periodontitis staging and grading using panoramic radiographs.

BMC oral health
BACKGROUND: Periodontal diseases are common chronic conditions that can lead to tooth loss and systemic complications if not diagnosed and treated promptly. The 2017 classification by the American Academy of Periodontology highlights the need for eff...

Large language models in clinical trials: applications, technical advances, and future directions.

BMC medicine
BACKGROUND: As clinical trials scale up and grow more complex, researchers are facing mounting challenges, including inefficient participant recruitment, complex data management, and limited risk monitoring. These issues not only increase the workloa...

Ensemble techniques for predictive modeling of leishmanial activity via molecular fingerprints.

BMC medical informatics and decision making
BACKGROUND: Leishmaniasis, a neglected tropical disease caused by Leishmania protozoan parasites and transmitted by sandflies, poses a significant global health challenge, especially in resource-limited environments. The life cycle of the parasite in...

Determinants of malaria transmission in Indian districts in 2018: insights from ensemble models.

Malaria journal
BACKGROUND: The National Framework for Malaria Elimination, formulated in 2016, aims to eliminate malaria in India by 2030, focusing on the districts as the strategic units for planning and implementing intervention measures. In this study, the spati...

Feasibility of machine learning analysis for the identification of patients with possible primary ciliary dyskinesia.

Orphanet journal of rare diseases
BACKGROUND: Significant diagnostic delays are common in primary ciliary dyskinesia (PCD), a rare disease that is significantly underdiagnosed. Scalable screening methods could improve early identification and health outcomes.

Statistical and machine-learning assessment of attitudinal, knowledge, and perceptual factors on diabetes awareness in Kuwait.

BMC medical informatics and decision making
OBJECTIVES: The primary objective was to identify and analyze the factors that impact diabetes awareness and perception among diabetic and non-diabetic participants. The study also sought to assess the effectiveness of current health awareness progra...

A scoping review of future research trends and priorities in health systems.

Health research policy and systems
BACKGROUND: Health systems worldwide are increasingly influenced by rapid and complex changes across various domains. Anticipating and responding to these changes is critical to ensuring the sustainability and effectiveness of health systems. Future-...

Machine learning model development and validation using SHAP: predicting 28-day mortality risk in pulmonary fibrosis patients.

BMC medical informatics and decision making
BACKGROUND: Early prediction of mortality risk within 28 days of admission is crucial for personalized treatment in patients with pulmonary fibrosis (PF). This study aims to develop a predictive model for 28-day mortality risk in PF patients using in...

Prevalence and factors associated with HIV drug resistance among adult persons living with HIV/AIDS in nine countries of Sub-Saharan Africa using population-based HIV impact assessments: 2015-2019.

BMC public health
INTRODUCTION: HIV drug resistance (HIVDR) remains a significant challenge in sub-Saharan Africa (SSA) due to limited effective Treatment and healthcare resources vary. Using the first widely available HIVDR surveillance data in SSA, we calculated the...

Prediction of intraductal cancer microinfiltration based on the hierarchical fusion of peri-tumor imaging histology and dual view deep learning.

BMC cancer
OBJECTIVE: The aim of this study was to develop a multimodal fusion model for accurate risk prediction and clinical decision support for ductal carcinoma in-situ (DCIS).