TS-075868 — Clinicians managing pediatric patients supported by a ventricular assist device must routinely assess pump performance by visually estimating membrane fill and ejection during pump cycles. These evaluations are critical for patient management but are inherently subjective, time-consuming, and pron…

TS-075489 — Organizations across healthcare, government, finance, market intelligence, and regulatory sectors routinely generate large collections of reports containing valuable tabular data. While these reports often follow consistent formats, extracting, comparing, and analyzing information across multiple …

TS-075230 — Problem Computed tomography (CT) is commonly used for its widespread availability, rapid acquisition times, and depiction of fine bony detail, but it struggles to differentiate spinal cord tissue from cerebrospinal fluid (CSF) due to their similar mass densities. Magnetic resonance imaging (MRI) of…

TS-075229 — Problem Artificial intelligence models often perform well during development but show unpredictable drops in accuracy and reliability when deployed on data that differ from their training sets. In high‑risk settings such as clinical care, these shifts can arise from changes in hardware, protocols…

TS-075184 — Problem Synthetic lethality (SL) is defined as a gene combination effect (GCE) of two genes where loss-of-function of both genes, rather than one, causes cell death. While carrying strong therapeutic potential in the treatment of cancer, SL interactions are context specific and sparse, thereby limi…

TS-075183 — Problem Current eligibility biomarkers for Immune checkpoint inhibitors (ICIs) poorly predict patient’s response. Drug clearance, both at baseline and over time, is a stronger predictor of ICI effectiveness, however the current non-linear mixed effects modeling (NLME) approach for estimating …

TS-075168 — Problem Metastasis is the primary driver of cancer-related deaths, yet accurately predicting its onset is a major clinical challenge. Current diagnostic tools often fail to detect occult metastatic cells and metastatic precursor cells, resulting in either overdiagnosis, with unnecessary treatments,…

TS-074767 — Chronic and complex wounds remain a major clinical and economic burden, with high infection rates, slow healing trajectories, and limited real-time monitoring capabilities. Conventional dressings are largely passive and do not adapt to dynamic wound environments, while existing advanced therapies …

TS-074669 — Current cardiac MRI workflows rely heavily on breath-holds, ECG gating, and retrospective binning, which break down in patients with arrhythmias, irregular breathing, or limited ability to cooperate. Existing 3D approaches often average away beat-to-beat variability or suffer from motion artifacts…

TS-074599 — Discovering molecules that simultaneously satisfy multiple competing design criteria is a resource-intensive challenge across the pharmaceutical, energy, and materials industries. The enormity of chemical space makes exhaustive screening impractical, while existing AI-guided methods either restric…

TS-074578 — The Need As AI systems are rapidly deployed across healthcare, education, and high-stakes decision-making, organizations lack rigorous tools to evaluate how humans actually interact with, trust, and respond to AI in real-world conditions. Opportunity Overview Researchers at the Ohio State Univ…

TS-074364 — Senior executives struggle to understand and prioritize cybersecurity risk in business terms. Existing vulnerability scoring systems rely on opaque or arbitrary measures that fail to connect cybersecurity decisions to financial impact, staffing costs, or operational tradeoffs. As a result, organiz…

TS-074095 — Hybrid and electrified vehicles face increasing pressure to simultaneously reduce fuel consumption and tailpipe emissions, particularly during transient operating conditions such as cold start. Conventional rule-based or static control strategies struggle to optimally manage the tradeoffs among en…

TS-073932 — DEEP Phaser enables fully automated, expert level phase correction to improve NMR data quality, consistency, and throughput across routine and high-volume workflows. Problem Overview Accurate phase correction is essential for reliable NMR interpretation and quantitative analysis. Despite its impo…

TS-073717 — Spiking Neural Networks (SNNs) promise ultra-low-power, low-latency AI for edge and neuromorphic computing, but their adoption is constrained by fundamental training challenges. SNN performance is highly sensitive to how training data are collected (e.g., lighting, sensor settings, noise), leading…

TS-073587 — Magnetic nanoparticles are widely used in applications such as magnetic hyperthermia, catalysis, sensing, and data storage, yet their performance is often limited by poor control over key magnetic properties. Existing materials typically rely on size or shape control alone, which provides limited …

TS-073225 — In today's world, we are increasingly using low-cost devices with limited resources (often referred to as "edge devices") which are supported by connected high-performance servers. However, these edge devices often can't handle complex tasks such as classifying data. To make this possible, we need…

TS-072175 — The Need Modern industrial and energy systems are increasingly complex, making timely fault detection and discrimination critical for safety, reliability, and cost control. Existing fault diagnosis methods often struggle with transient states, require extensive historical data, or lack interpretabil…

TS-071386 — The Need The search for sustainable, high-performance battery materials is hindered by reliance on finite metal-based resources and slow, trial-and-error development cycles. Organic electrode materials (OEMs), composed of earth-abundant elements, offer a more sustainable path but present challenges …

TS-071267 — The Need Modeling solvent effects on catalytic surfaces is critical for designing industrial processes like biomass conversion, fuel synthesis, and electrocatalysis. Traditional multiscale simulations combining density functional theory (DFT) and molecular dynamics (MD) offer accuracy but are comp…

TS-070954 — The Need Intersections are among the most dangerous areas on U.S. roadways, accounting for approximately 25% of traffic fatalities and nearly half of all injuries annually. Vulnerable Road Users (VRUs), including pedestrians and cyclists, face increasing risk due to complex traffic dynamics and limi…

TS-069654 — Technology bundle containing T2025-148 and T2024-150.

TS-069523 — The Need In many scientific and industrial fields, there is a critical need for interpretable and accurate models that can be derived from complex datasets. Traditional machine learning methods often produce black-box models that lack transparency and interpretability, making it difficult to unders…

TS-068443 — In high-stakes industries, the integration of humans and advanced automation systems demands evaluation methods that reliably predict performance under varying challenges. Current testing methods often focus on individual components, failing to assess how human-machine teams operate as a unit, par…

TS-067550 — A method to improve the performance and accuracy of ML-based decision trees.

TS-066063 — Our cybersecurity vulnerability maintenance system stands as a pillar of modern security strategy, transforming reactive security measures into a preemptive defense mechanism. This integration of technology and economics ensures that your most critical assets are protected efficiently and effectively, making it an invaluable tool for any organization serious about security.

TS-066058 — By adopting our AI-driven solution, engineering teams can achieve more in less time, push the boundaries of innovation, and significantly cut down costs, all while maintaining or increasing the reliability and accuracy of their structural and material analysis. This is not just an evolution in FEM technology—it's a revolution.

TS-065447 — The Need: In the realm of nonlinear control engineering, managing systems with chaotic dynamics poses a significant challenge. Conventional methods often fall short in achieving precise control over such systems due to their complexity and unpredictability. There's a pressing need for a solutio…

TS-065446 — The Need: In today's fast-paced commercial landscape, there's an increasing demand for rapid processing of complex data sets. Traditional computing methods often struggle to keep pace with real-time requirements, leading to inefficiencies and missed opportunities. Addressing this need for sw…

TS-063238 — A novel regularization technique applicable for medical imaging applications that leverages conditional generative adversarial networks (cGANs) to generate reconstructed images in significantly shorter timeframes. The Need Several techniques are used for image reconstruction in the medical aren…

TS-063237 — Electronic Health Records (EHR) are used in over 88% of all US medical clinics to improve care and streamline data. In addition, they enable sharing of data to multiple providers dealing with the same patient, thereby enhancing efficiency and care. The Need In the last decade, medical practices…

TS-063154 — Worldwide, 686,000 new head and neck (H&N) cancers are diagnosed yearly, and 375,000 people will die annually. Human papillomavirus (HPV) is responsible for an increasing subset of H&N malignancies called oropharyngeal squamous cell carcinomas (OPSCC). Although it has a better prognosis than…

TS-063039 — Medical-based AI systems have seen increased use in recent years across a range of applications (e.g., diagnostics, prognostics, treatment response prediction). Their widespread adoption by the medical community is still restricted, primarily due to their limited ability to realize a high degree of …

TS-063038 — The Need In the era of machine learning, high-stakes decisions are increasingly being made by black box models, leading to concerns about accountability and fairness. These models can exhibit inherent biases, raising the need for a system that ensures accountability and fairness in decision-making …

TS-063007 — The Need In disaster-stricken areas, timely and accurate reconnaissance is paramount for effective response and recovery efforts. Traditional methods of assessing damage to critical infrastructure, such as power distribution poles, often involve time-consuming manual inspections, leading to delays …

TS-062764 — The Pulmonary Hypertension Outcomes Risk Assessment (PHORA): a PAH risk stratification tool.

TS-062576 — The Need Like a molecular “fingerprint”, NMR spectra provide valuable insights into the properties and structures of molecular compounds. However, analyzing and interpreting NMR spectra is inherently challenging as comprehensive and explicit identification of a compound is tedious and t…

TS-062574 — The Need Like a molecular “fingerprint”, NMR spectra provide valuable insights into the properties and structures of molecular compounds. However, analyzing and interpreting NMR spectra is inherently challenging as comprehensive and explicit identification of a compound is tedious and t…

TS-060092 — AI methods and systems for predicting reactants and their synthesis paths to support drug design and chemical synthesis.

TS-051417 — Traditional regression analysis has been a staple in predicting cause-effect relationships. Counltess industries use these methods to predict rare events, from economic issues to cancer research, causality is often a desired result. Given the vast amount of potential variables it sometimes becomes…