Search Tag: ML
2025 09 Jul
Hospital-onset bacteraemia and fungaemia (HOB) are frequent, often preventable hospital complications linked to high mortality, morbidity, and costs. While many studies have focused on patient-related, non-modifiable factors (e.g., demographics, comorbidities), these offer limited prevention opportunities. Since up to two-thirds of HOB ca1Read more
2025 11 Jun
Advancements in civilian casualty care can reduce mortality from trauma, particularly those due to airway compromise or prehospital haemorrhage. Timely delivery of lifesaving interventions (LSIs) is crucial but challenging for prehospital medics, who must make rapid decisions under constrained conditions with limited experience and unreliable tria1Read more
2024 06 Feb
Hospitals utilise unscheduled return visit (URV) rates in emergency departments (EDs) to determine care quality. Higher rates lead to increased costs and longer wait times for patients who need immediate care. Frequent ED visits also contribute to overcrowding, causing treatment delays and higher mortality rates. Developing predictive m1Read more
2023 13 Nov
The integration of Information Technology (IT) in the healthcare sector is a beacon of transformation amidst modern challenges. This article illuminates the role of Artificial Intelligence (AI), Machine Learning (ML), Natural Language Processing (NLP), and low-code solutions in healthcare. By exploring real-world examples and statistics, we shed l1Read more
2023 13 Nov
The integration of Information Technology (IT) in the healthcare sector is a beacon of transformation amidst modern challenges. This article illuminates the role of Artificial Intelligence (AI), Machine Learning (ML), Natural Language Processing (NLP), and low-code solutions in healthcare. By exploring real-world examples and statistics, we shed l1Read more
2023 13 Nov
The integration of Information Technology (IT) in the healthcare sector is a beacon of transformation amidst modern challenges. This article illuminates the role of Artificial Intelligence (AI), Machine Learning (ML), Natural Language Processing (NLP), and low-code solutions in healthcare. By exploring real-world examples and statistics, we shed l1Read more
2023 13 Nov
The integration of Information Technology (IT) in the healthcare sector is a beacon of transformation amidst modern challenges. This article illuminates the role of Artificial Intelligence (AI), Machine Learning (ML), Natural Language Processing (NLP), and low-code solutions in healthcare. By exploring real-world examples and statistics, we shed l1Read more
2019 13 Nov
Summary: Where do the computer sciences have the potential to reduce radiologist burnout, reduce costs and make workflow more efficient and what are the first steps in implementing the technology? In the long-term future, I think that computers will take over the work of image interpretation from humans, just as computer1Read more
2019 26 Aug
Summary: Combine the characteristic of our engagement with social media with existing technology and how we could improve patient compliance in the not so distant future. Patient treatment compliance is a significant barrier and a challenge for healthcare professionals the world over. While several studies have been conducted leading to1Read more