Healthcare AI

By pairing AI-generated content with a hybrid human-AI review process and a knowledge-graph-driven personalization layer, GeniX delivers exam prep that scales without scaling cost, while pinpointing the root cause of each learner's mistakes.

It uses the same knowledge graph to keep its responses clinically accurate and on-topic, avoiding the generic, unconstrained behavior of general-purpose AI assistants.

GeniX is a generative AI platform that generates, validates, and personalizes clinical certification exam content, moving beyond static, human-authored question banks into a continuously expanding, self-refining question engine designed for autonomous content generation.

This innovation is an AI-powered surgical management system that integrates a surgeon-facing application with real-time computer vision to optimize instrument and supply utilization.

The technology consists of two integrated components: an EMR-agnostic mobile and web application and an AI-enabled computer vision monitoring system.

A unique aspect of this AI is its Scale-Noise Space Augmented Learning (SNSAL) strategy, which trains the system to recognize instruments accurately despite varied magnifications, orientations, and low-light conditions common in operating rooms.

University of Pittsburgh researchers are developing novel software, spatiAlytica, an AI-powered user-friendly system for analysis of spatial transcriptomics (ST) data.

An AI-powered software, spatiAlytica, is being developed to assist biologists with analysis of ST data.

spatiAlytica is designed to work as an AI informatician.

Note2Data is an AI-driven software system that automatically converts unstructured orthopedic clinical notes and surgical reports into clean, structured research data.

Note2Data leverages artificial intelligence to identify and extract predefined research variables from free-text medical documentation — including clinic notes and operative reports — transforming narrative content into standardized datasets ready for research analysis.

- Domain-governed AI framework minimizes inter-reviewer variability and human error.

By enabling precise, language-driven customization of 3D environments, it provides an unprecedented tool for evaluating and training AI systems on visual spatial reasoning tasks.

InfiniBench addresses a critical gap in AI evaluation by generating diverse, controllable 3D scene benchmarks from simple natural language prompts.

Unlike static or narrowly scoped benchmarks, InfiniBench can generate an essentially infinite range of complexity levels, enabling researchers and developers to isolate specific AI failure modes, stress-test models under precisely defined spatial conditions, and produce high-quality synthetic training data on demand.

Two built-in ethical checkpoints aligned with four core pillars of AI ethics and professional codes ensure that client resources and treatment plans produced with generative AI maintain safety, reliability and professionalism.

It stands out by integrating ethical oversight directly into both prompt design and output review, a feature often missing in general AI guidelines.

• Examining academic work for AI generated text.

A University of Pittsburgh researcher has developed a method, Turing Auditing, to accurately detect the presence of text produced by generative artificial intelligence (GenAI) in a work product.

Through the combination of proprietary forensic and investigative reading techniques alongside commercially available AI tools, Turing Auditing can be used to assess any written work product (e.

International Journal of Artificial Intelligence in Education, 35(2), 879–913.

This invention provides a method for identifying patients with, or at risk of, severe asthma by measuring the expression of specific airway genes or related protein glycosylation and keratin markers in patient samples.

This invention is an autonomous alignment system for multipass optical cavities (Herriott cells) used in precision gas sensing, leveraging a lightweight machine learning model and real-time camera feedback to detect and correct mirror misalignment without human intervention.

This invention is an advanced clinical decision support system that utilizes machine learning to determine optimal radiotherapy doses and predict survival outcomes for patients undergoing brain radiosurgery.

- Precision Behavioral Health Analytics: Integration into platforms and software focused on improving patient outcomes through real-world data and artificial intelligence.

NeuroSmart is an AI-driven clinical decision support system (CDSS) designed to optimize stroke management by providing personalized, real-time diagnostic and treatment recommendations.

js, allows clinicians to input patient data and receive AI-generated recommendations with confidence scores and visual analytics.

- Enhances clinical decision-making with AI-driven insights tailored to patient-specific factors.

Utilizing artificial intelligence (AI), SLAID analyzes source material, generates customized presentation outlines based on specified contexts, and evaluates recorded presentations for alignment with the outline and cognitive demand levels.

SLAID is a software tool that leverages AI and Natural Language Processing (NLP) to assist users in creating and analyzing presentations.

Key features include document upload/search, AI-powered document analysis, contextual presentation outline generation, an editable checklist, integrated recording tools, AI-driven presentation analysis, feedback and reporting, and secure video handling.

University of Pittsburgh research has developed Perepex, an AI-powered educational platform designed to facilitate video-based learning and assessment between teachers and students.

By leveraging AI for real-time transcription, cognitive analysis, and personalized feedback, Perepex aims to improve educational outcomes and streamline the assessment process.

Perepex is a software platform that utilizes AI to enhance video-based learning and assessment.