Ovarian lesions are frequently detected, often by chance, and managing them is crucial to avoid delayed diagnoses or unnecessary interventions. While transvaginal ultrasound is the primary diagnostic tool for distinguishing benign from malignant lesions, its accuracy heavily relies on the examiner’s expertise. A shortage of skilled ultrasound professionals exacerbates diagnostic delays, particularly as biopsies are…
The development of Physical AI—AI systems designed to simulate, predict, and optimize real-world physics—has long been constrained by significant challenges. Building accurate models often demands extensive computational resources and time, with simulations sometimes requiring days or weeks to produce actionable results. Additionally, the complexity of scaling these systems for practical use across industries such as…
Dense embedding-based text retrieval has become the cornerstone for ranking text passages in response to queries. The systems use deep learning models for embedding text into vector spaces that enable semantic similarity measurements. This method has been adopted widely in applications such as search engines and retrieval-augmented generation (RAG), where retrieving accurate and contextually relevant…
In a time when global health faces persistent threats from emerging pandemics, the need for advanced biosurveillance and pathogen detection systems is increasingly evident. Traditional genomic analysis methods, while effective in isolated cases, often struggle to address the complexities of large-scale health monitoring. A significant challenge is identifying and understanding the genomic diversity in environments…
Predicting transcriptomes directly from genome sequences is a significant challenge in microbial genomics, particularly for the numerous sequenced microbes that remain unculturable or require complex experimental protocols like RNA-seq. The gap between genomic information and functional understanding leaves us without knowledge of the microbial adaptive processes, survival mechanisms, and gene regulation functions. This must be…
When it comes to AI tools, chatbots are often the first thing that comes to mind —conversation-based interfaces for users to write queries and receive responses. These dialogue interfaces are certainly useful, but they aren’t always the best fit for handling our everyday work. Often tacked on to the side of our workflows, chatbots supplement…
Disaggregated systems are a new type of architecture designed to meet the high resource demands of modern applications like social networking, search, and in-memory databases. The systems intend to overcome the physical restrictions of the traditional servers by pooling and managing resources like memory and CPUs among multiple machines. Flexibility, better utilization of resources, and…
Using LLMs in clinical diagnostics offers a promising way to improve doctor-patient interactions. Patient history-taking is central to medical diagnosis. However, factors such as increasing patient loads, limited access to care, brief consultations, and the rapid adoption of telemedicine—accelerated by the COVID-19 pandemic—have strained this traditional practice. These challenges threaten diagnostic accuracy, underscoring the need…