Latest AI and machine learning research in information technology for healthcare professionals.
Generative Artificial Intelligence (GenAI) is rapidly reshaping the global financial landscape, offering unprecedented opportunities to enhance customer engagement, automate complex workflows, and extract actionable insights from vast financial data. This survey provides an overview of GenAI adoption across the financial ecosystem, examining how banks, insurers, asset managers, and fintech start...
Unsupervised novelty detection (UND), aimed at identifying novel samples, is essential in fields like medical diagnosis, cybersecurity, and industrial quality control. Most existing UND methods assume that the training data and testing normal data originate from the same domain and only consider the distribution variation between training data and testing data. However, in real scenarios, it is ...
In the rapidly evolving landscape of cybersecurity threats, ransomware represents a significant challenge. Attackers increasingly employ sophisticat...
The lack of standardized evaluation benchmarks in the medical domain for text inputs can be a barrier to widely adopting and leveraging the potentia...
Flexible sharing of electronic medical records (EMRs) is an urgent need in healthcare, as fragmented storage creates EMR management complexity for b...
Large language models (LLMs) hold great promise for medical applications and are evolving rapidly, with new models being released at an accelerated ...
The rapid evolution of malware variants requires robust classification methods to enhance cybersecurity. While Large Language Models (LLMs) offer po...
Phishing attacks represent an increasingly sophisticated and pervasive threat to individuals and organizations, causing significant financial losses...
Recent advancements in image manipulation have achieved unprecedented progress in generating photorealistic content, but also simultaneously elimina...
Clinical language models have achieved strong performance on downstream tasks by pretraining on domain specific corpora such as discharge summaries ...
Medication recommendation is crucial in healthcare, offering effective treatments based on patient's electronic health records (EHR). Previous studi...
Data from domains such as social networks, healthcare, finance, and cybersecurity can be represented as graph-structured information. Given the sens...
Synthetic Electronic Health Record (EHR) time-series generation is crucial for advancing clinical machine learning models, as it helps address data ...
The complexities of healthcare data, including privacy concerns, imbalanced datasets, and interoperability issues, necessitate innovative machine le...
Migraine is a common but complex neurological disorder that doubles the lifetime risk of cryptogenic stroke (CS). However, this relationship remains...
Since the 1990s, the integration of technology into daily life has led to the creation of an extensive network of interconnected devices, transformi...
Birth weight (BW) is a key indicator of neonatal health, with low birth weight (LBW) linked to increased mortality and morbidity. Early prediction o...
A scalable and reliable system is required to analyze the National Health and Nutrition Examination Survey (NHANES) data efficiently to understand h...
Modern identity verification systems increasingly rely on facial images embedded in biometric documents such as electronic passports. To ensure glob...
Cancer detection and prognosis relies heavily on medical imaging, particularly CT and PET scans. Deep Neural Networks (DNNs) have shown promise in t...