Latest AI and machine learning research in bioterrorism for healthcare professionals.
Computer vision methods offer great potential for rapid image-based identification of medically important arthropod specimens. However, imaging large numbers of specimens is time consuming, and it is difficult to achieve the high image quality required for machine learning models. Conventional imaging methods for identifying and digitizing arthropods, such as insects and spiders, use a stereomicro...
Cholera continues to pose a significant public health challenge in Nigeria, driven by socioeconomic disparities, poor sanitation, and environmental factors such as recurrent flooding. This narrative review examines cholera outbreaks in Nigeria, exploring epidemiological trends, socioeconomic and meteorological drivers, and advancements in diagnostic technologies. Emphasis is placed on the role of ...
Parkinson's disease (PD) is a common and debilitating neurodegenerative disorder. The inflammatory response is essential in the pathogenesis and progr...
Accurately predicting individual antidepressant treatment response could expedite the lengthy trial-and-error process of finding an effective treatmen...
Due to considerable tumour heterogeneity, stomach adenocarcinoma (STAD) has a poor prognosis and varies in response to treatment, making it one of the...
Placebo effect represents a serious confounder for the assessment of treatment effect to the extent that it has become increasingly difficult to devel...
In the quest to ensure adequate preparedness for health emergencies caused by infectious disease pandemics, there is a need for tools that can address...
Machine learning models for speech-based depression classification offer promise for health care applications. Despite growing work on depression cl...
In the early stage of an infectious disease outbreak, public health strategies tend to gravitate towards non-pharmaceutical interventions (NPIs) giv...
Large-scale crises, including wars and pandemics, have repeatedly shaped human history, and their simultaneous occurrence presents profound challeng...
Recent studies have raised significant concerns regarding the vulnerability of Large Vision Language Models (LVLMs) to maliciously injected or pertu...
Large Language Models (LLMs) are increasingly used in production systems, powering applications such as chatbots, summarization, and question answer...
Understanding the effects of quarantine policies in populations with underlying social networks is crucial for public health, yet most causal infere...
Complex networks are susceptible to contagious cascades, underscoring the urgency for effective epidemic mitigation strategies. While physical quarant...
SUMMARY: Accurate drug response prediction is critical to advancing precision medicine and drug discovery. Recent advances in deep learning (DL) have ...
Segmentation of Earth observation (EO) satellite data is critical for natural hazard analysis and disaster response. However, processing EO data at ...
Neoadjuvant chemotherapy (NAC) response prediction for triple negative breast cancer (TNBC) patients is a challenging task clinically as it requires...
Fungal keratitis is a severe vision-threatening corneal infection with a prognosis influenced by fungal virulence and the host's immune defense mech...
GPT-4o is an autoregressive omni model that accepts as input any combination of text, audio, image, and video, and generates any combination of text...
This paper presents a rapid approach to assessing disaster resilience in Florida, particularly regarding Hurricane Helene (2024). This category four...