249 Results were found on Technologies
Sub Category Name
Eco-Friendly, Lignin-free Cellulose Scaffolds from Green Macroalgae for Biomedical Applications
Unmet Need • Sustainability: there is a need for materials supply that is both biocompatible and eco-friendly • Engineering constraints: many available cellulose scaffolds lack tunable structural features (e.g., pore size, fiber orientation) that closely mimic native extracellular matrices (ECM) for specific tissue engineering uses • Cost: bacterial cellulose (used for wound dressings and tissue […] Read More >
DeepMonC: Ultrafast Quantitative MRI via Vision Transformers
Current MRI techniques face significant limitations due to lengthy scan times, limited accessibility, and challenges in achieving comprehensive, high-quality tissue characterization. Techniques like saturation transfer MRI and multi-contrast protocols, while offering rich biochemical information, are hindered by time-consuming, multi-sequence acquisitions and often struggle with hardware-related artifacts and consistency across sites. This results in an inefficient […] Read More >
Smartwatch-Informed Participant Matching and Outcome Optimization in Clinical Trials
Randomized controlled trials (RCTs) carry prohibitive costs of up to hundreds of thousands of dollars per participant. Traditional matching approaches relying solely on general health status, disease progression, and demographic factors fail to optimize statistical accuracy, resulting in larger-than-necessary trials at high costs. Technology • A Smartwatch-Informed Matching (SIM) protocol for enhanced clinical trial design […] Read More >
A Novel Model for Estimating Hair Cell Loss from Audiograms Using a Nonlinear Cochlear Model
Age-related hearing loss (presbycusis) is prevalent and multifactorial, but current clinical tools cannot precisely differentiate between the underlying cochlear pathologies (e.g., sensory vs. metabolic loss). There is also a scarcity of non-invasive, quantitative methods to estimate the extent and location of hair cell loss in living patients, limiting personalized treatment and research into hearing loss […] Read More >
Automatic Fitting System for 3D Printing of Splints
Unmet Need Upper limb injuries frequently require splints for rehabilitation and support. Current options are limited, and include: Off-the-shelf splints: Not tailored to individual anatomy, may not fit or provide the required biomechanical action. Hand-made splints: Require skilled clinicians, are time-consuming, and occupy the clinician during fabrication, delaying 3D-printed splints are promising but demand advanced […] Read More >
Noncoding RNA-Based Strategy for Diagnosis and Monitoring of Pancreatic Cancer
Pancreatic Ductal Adenocarcinoma (PDAC) is one of the deadliest forms of cancer, with a five-year survival rate of less than 10%. A major contributor to this high mortality is the lack of effective tools for early detection — the disease is typically diagnosed at an advanced, often inoperable stage. Current diagnostic approaches, including imaging and […] Read More >
Automated Follicle Tracking via Home-Use Ultrasound- Enhancing Fertility Monitoring with AI
While ultrasound is widely used during pregnancy, its role in pre-conception—particularly for follicle tracking—is equally critical. In fertility treatments like IVF and IUI, timing ovulation is key. This relies on frequent, accurate monitoring of follicle development. Currently, this is performed through manual 2D ultrasound scans in clinical settings, which are: Time-consuming, operator-dependent and inconvenient for […] Read More >
Structure-Guided Platform for Allosteric Inhibition of HECT E3 Ligases
Targeting “Pocketless” Enzymes to Treat Cancer, Immune, and Other Diseases Short Description: Our platform enables the selective inhibition of HECT E3 ubiquitin ligases, key regulators of protein degradation-through a novel allosteric mechanism. Using advanced structural biology and machine learning-driven screening, we access a previously unreachable druggable space. Lead compounds identified by this approach have demonstrated […] Read More >
Execution Guided Line-by-Line Code Generation
Large language models (LLMs) have revolutionized the field of code generation, demonstrating impressive capabilities in automating programming tasks and assisting developers. Despite these advancements, current methods primarily rely on pattern recognition from static code representations, often producing syntactically plausible but functionally incorrect code. Many of these models lack the ability to explicitly reason about runtime […] Read More >
Overclocking LLM Reasoning- Monitoring and Controlling Thinking Path Lengths in LLMs
Large Language Models (LLMs) like ChatGPT have revolutionized AI-powered reasoning, enabling applications across diverse domains. However, their internal reasoning processes often remain opaque, leaving users in the dark about how long the model will take to arrive at an answer. UNMET NEED Currently, users interact with reasoning models without any indication of the internal progress […] Read More >
