Multilingual B2B Supplier Detection and Information Extraction

At Tealbook, we search the web to make the world’s business-to-business supplier websites readily accessible. We extract important sentences and keywords to create a searchable database that buyers can then use to find the right supplier for their needs. But right now, we are limited to servicing English-language organizations. Can we expand our services to […]

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iStandardize: Recommendations for Healthcare Form Standardiz

iStandardize is an AI-powered machine learning solution that is designed to streamline the standardization of clinical order sets (i.e., forms) by using machine learning and natural language processing techniques. Currently, hospital networks use multiple versions of forms and order sets, many of them are similar in nature. The lack of standardization poses a challenge in […]

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Thales – Prédiction logistique en pharmacie

Les pharmacies au détail s’appuient principalement sur leurs propres données empiriques pour planifier et prévoir leurs stocks. Ce type de données a ses propres caractéristiques, qui peuvent être saisonnières et être affectées par des événements spéciaux et imprévus tels que les maladies pandémiques. Toutefois, à mesure que la quantité de données s’accumule, il n’est pas […]

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Interpretable Machine Learning for Predictive Analytics in Employee Benefits Insurance

In recent years, many machine learning methods have been developed for predictive analytics and automated decision making. However, the lack of explanation resulted in both practical and ethical issues. In this project, we will employ and advance interpretable machine learning methods for various predictive analytics tasks in employee benefit insurance. The proposed methods can be […]

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Explore efficiently automated parallel hyperparameter search for optimizing machine learning models over large scale cloud cluster

Machine learning has been applied in various fields and shown promising results in recent years. Researchers have found that tuning machine learning models in a proper way can vastly boost the model performance with respect to the specific AI task. However, tuning machine learning models at scale, especially finding the right hyperparameter values, can be […]

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An Investigation of Service Mesh(es) and Security Models Within and Across Multiple Distributed Systems

Global service providers in highly regulated financial sectors must accommodate an ever-changing, sometimes competing, landscape of regulatory concerns. This project seeks to determine a reasonable path forward in technology design and adoption to accommodate current and anticipated infrastructure changes. Moreover, bridging the service layer across multiple, distinct distributed systems of varying complexity will pose new […]

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Applied Machine Learning for Early Detection of Retinal Toxicity

Hydroxychloroquine (HCQ) is an anti-inflammatory drug that is widely prescribed for a range of auto-immune disorders such as lupus and rheumatoid arthritis. An unwanted side effect of long-term use of HCQ is vision loss by retinal toxicity. If detected early, it could lead to early intervention to prevent vision loss and improve the quality of […]

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Machine Learning for Cancer Treatment Plan Benchmarking

Oncology specialists are few in numbers and cannot be present within every hospital or clinic providing their guidance and support. There are institutions in this world with oncology experts that can provide the best possible care and the knowledge of these experts is stored in medical case files within the hospital. With the power of […]

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Forum Representation for Cross-Domain Recommendation

An internet forum is an online site for people to have conversations. It contains threads to hold discussions between users. Recommending appropriate threads to forum users is one of the main goals of an internet forum. To provide positive user experience, cross-domain thread recommendation is required, which can be benefited greatly from the help of […]

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