Publications by authors named "I Hoyer"

Objective: In recent years, wearable devices such as smartwatches and smart patches have revolutionized biosignal acquisition and analysis, particularly for monitoring electrocardiography (ECG). However, the limited power supply of these devices often precludes real-time data analysis on the patch itself.

Approach: This paper introduces a novel Python package, tinyHLS (High Level Synthesis), designed to address these challenges by converting Python-based AI models into platform-independent hardware description language (HDL) code accelerators.

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The Anopheles gambiae 1000 Genomes (Ag1000G) Consortium previously utilized deep sequencing methods to catalogue genetic diversity across African An. gambiae populations. We analyzed the complete datasets of 1142 individually sequenced mosquitoes through Microsoft Premonition's Bayesian mixture model based (BMM) metagenomics pipeline.

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Atrial Fibrillation (AF) is one of the most common heart arrhythmias. It is known to cause up to 15% of all strokes. In current times, modern detection systems for arrhythmias, such as single-use patch electrocardiogram (ECG) devices, have to be energy efficient, small, and affordable.

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Background: Initial systemic therapy for patients with metastatic colorectal cancer (mCRC) is usually based on two- or three-drug chemotherapy regimens with fluoropyrimidine (5-fluorouracil (5-FU) or capecitabine), oxaliplatin and/or irinotecan, combined with either anti-VEGF (bevacizumab) or, for RAS wild-type (WT) tumors, anti-EGFR antibodies (panitumumab or cetuximab). Recommendations for patients who are not eligible for intensive combination therapies are limited and include fluoropyrimidine plus bevacizumab or single agent anti-EGFR antibody treatment. The use of a monochemotherapy concept of trifluridine/ tipiracil in combination with monoclonal antibodies is not approved for first-line therapy, yet.

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Monitoring the presence and spread of pathogens in the environment is of critical importance. Rapid detection of infectious disease outbreaks and prediction of their spread can facilitate early responses of health agencies and reduce the severity of outbreaks. Current sampling methods are sorely limited by available personnel and throughput.

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