# Microsoft (United States)

**Type:** Institutions  
**Canonical URL:** https://scholariq.org/institutions/microsoft-united-states/

## Facts

| Field | Value |
| --- | --- |
| Avg h-index | 64.9 |
| Citations | 4,603,487 |
| City | Redmond |
| Country | US |
| Description | Microsoft (United States) is a research organisation in Redmond, US. OpenAlex records 34,805 works and 4,603,487 citations for it. 5,076 researchers list it as their most recent affiliation. |
| Homepage | https://www.microsoft.com/en-us |
| OpenAlex ID | https://openalex.org/I1290206253 |
| Region | Washington |
| Researchers | 5,076 |
| ROR ID | https://ror.org/00d0nc645 |
| Type | company |
| Wikidata ID | Q2283 |
| Works | 34,805 |

## University papers

Showing 12 of 30.

- [International evaluation of an AI system for breast cancer screening](https://scholariq.org/papers/international-evaluation-of-an-ai-system-for-breast-cancer-screening/)
- [Scientific discovery in the age of artificial intelligence](https://scholariq.org/papers/scientific-discovery-in-the-age-of-artificial-intelligence/)
- [The use of clinical risk factors enhances the performance of BMD in the prediction of hip and osteoporotic fractures in men and women](https://scholariq.org/papers/the-use-of-clinical-risk-factors-enhances-the-performance-of-bmd-in-the/)
- [Population-Based Study of Survival after Osteoporotic Fractures](https://scholariq.org/papers/population-based-study-of-survival-after-osteoporotic-fractures/)
- [Benign Breast Disease and the Risk of Breast Cancer](https://scholariq.org/papers/benign-breast-disease-and-the-risk-of-breast-cancer/)
- [Diagnostic accuracy of deep learning in medical imaging: a systematic review and meta-analysis](https://scholariq.org/papers/diagnostic-accuracy-of-deep-learning-in-medical-imaging-a-systematic-review-and/)
- [Increased risk of cognitive impairment or dementia in women who underwent oophorectomy before menopause](https://scholariq.org/papers/increased-risk-of-cognitive-impairment-or-dementia-in-women-who-underwent/)
- [Large Language Model Influence on Diagnostic Reasoning](https://scholariq.org/papers/large-language-model-influence-on-diagnostic-reasoning/)
- [DHEA in Elderly Women and DHEA or Testosterone in Elderly Men](https://scholariq.org/papers/dhea-in-elderly-women-and-dhea-or-testosterone-in-elderly-men/)
- [Self-supervised learning for medical image classification: a systematic review and implementation guidelines](https://scholariq.org/papers/self-supervised-learning-for-medical-image-classification-a-systematic-review/)
- [GLoRIA: A Multimodal Global-Local Representation Learning Framework for Label-efficient Medical Image Recognition](https://scholariq.org/papers/gloria-a-multimodal-global-local-representation-learning-framework-for-label/)
- [Stratification of Breast Cancer Risk in Women With Atypia: A Mayo Cohort Study](https://scholariq.org/papers/stratification-of-breast-cancer-risk-in-women-with-atypia-a-mayo-cohort-study/)

## University researchers

- [Jun Takamatsu](https://scholariq.org/researchers/jun-takamatsu/)

## University top topics

Showing 8 of 25.

- [Topic Modeling](https://scholariq.org/topics/topic-modeling/)
- [Natural Language Processing Techniques](https://scholariq.org/topics/natural-language-processing-techniques/)
- [Parallel Computing and Optimization Techniques](https://scholariq.org/topics/parallel-computing-and-optimization-techniques/)
- [Cloud Computing and Resource Management](https://scholariq.org/topics/cloud-computing-and-resource-management/)
- [Software Engineering Research](https://scholariq.org/topics/software-engineering-research/)
- [Distributed systems and fault tolerance](https://scholariq.org/topics/distributed-systems-and-fault-tolerance/)
- [Advanced Image and Video Retrieval Techniques](https://scholariq.org/topics/advanced-image-and-video-retrieval-techniques/)
- [Data Management and Algorithms](https://scholariq.org/topics/data-management-and-algorithms/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.