| 1. |
- Leisawitz, David, et al.
(author)
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Origins Space Telescope: Baseline mission concept
- 2021
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In: Journal of Astronomical Telescopes, Instruments, and Systems. - 2329-4221 .- 2329-4124. ; 7:1
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Journal article (peer-reviewed)abstract
- The Origins Space Telescope will trace the history of our origins from the time dust and heavy elements permanently altered the cosmic landscape to present-day life. How did galaxies evolve from the earliest galactic systems to those found in the Universe today? How do habitable planets form? How common are life-bearing worlds? To answer these alluring questions, Origins will operate at mid-and far-infrared (IR) wavelengths and offer powerful spectroscopic instruments and sensitivity three orders of magnitude better than that of the Herschel Space Observatory, the largest telescope flown in space to date. We describe the baseline concept for Origins recommended to the 2020 US Decadal Survey in Astronomy and Astrophysics. The baseline design includes a 5.9-m diameter telescope cryocooled to 4.5 K and equipped with three scientific instruments. A mid-infrared instrument (Mid-Infrared Spectrometer and Camera Transit spectrometer) will measure the spectra of transiting exoplanets in the 2.8 to 20 μm wavelength range and offer unprecedented spectrophotometric precision, enabling definitive exoplanet biosignature detections. The far-IR imager polarimeter will be able to survey thousands of square degrees with broadband imaging at 50 and 250 μm. The Origins Survey Spectrometer will cover wavelengths from 25 to 588 μm, making wide-area and deep spectroscopic surveys with spectral resolving power R ∼ 300, and pointed observations at R ∼ 40,000 and 300,000 with selectable instrument modes. Origins was designed to minimize complexity. The architecture is similar to that of the Spitzer Space Telescope and requires very few deployments after launch, while the cryothermal system design leverages James Webb Space Telescope technology and experience. A combination of current-state-of-the-art cryocoolers and next-generation detector technology will enable Origins' natural background-limited sensitivity.
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| 2. |
- Ali, Sharib, et al.
(author)
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A multi-centre polyp detection and segmentation dataset for generalisability assessment.
- 2023
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In: Scientific data. - : Springer Science and Business Media LLC. - 2052-4463. ; 10:1
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Journal article (peer-reviewed)abstract
- Polyps in the colon are widely known cancer precursors identified by colonoscopy. Whilst most polyps are benign, the polyp's number, size and surface structure are linked to the risk of colon cancer. Several methods have been developed to automate polyp detection and segmentation. However, the main issue is that they are not tested rigorously on a large multicentre purpose-built dataset, one reason being the lack of a comprehensive public dataset. As a result, the developed methods may not generalise to different population datasets. To this extent, we have curated a dataset from six unique centres incorporating more than 300 patients. The dataset includes both single frame and sequence data with 3762 annotated polyp labels with precise delineation of polyp boundaries verified by six senior gastroenterologists. To our knowledge, this is the most comprehensive detection and pixel-level segmentation dataset (referred to as PolypGen) curated by a team of computational scientists and expert gastroenterologists. The paper provides insight into data construction and annotation strategies, quality assurance, and technical validation.
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| 3. |
- Ali, Sharib, et al.
(author)
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Assessing generalisability of deep learning-based polyp detection and segmentation methods through a computer vision challenge
- 2024
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In: SCIENTIFIC REPORTS. - 2045-2322. ; 14:1
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Journal article (peer-reviewed)abstract
- Polyps are well-known cancer precursors identified by colonoscopy. However, variability in their size, appearance, and location makes the detection of polyps challenging. Moreover, colonoscopy surveillance and removal of polyps are highly operator-dependent procedures and occur in a highly complex organ topology. There exists a high missed detection rate and incomplete removal of colonic polyps. To assist in clinical procedures and reduce missed rates, automated methods for detecting and segmenting polyps using machine learning have been achieved in past years. However, the major drawback in most of these methods is their ability to generalise to out-of-sample unseen datasets from different centres, populations, modalities, and acquisition systems. To test this hypothesis rigorously, we, together with expert gastroenterologists, curated a multi-centre and multi-population dataset acquired from six different colonoscopy systems and challenged the computational expert teams to develop robust automated detection and segmentation methods in a crowd-sourcing Endoscopic computer vision challenge. This work put forward rigorous generalisability tests and assesses the usability of devised deep learning methods in dynamic and actual clinical colonoscopy procedures. We analyse the results of four top performing teams for the detection task and five top performing teams for the segmentation task. Our analyses demonstrate that the top-ranking teams concentrated mainly on accuracy over the real-time performance required for clinical applicability. We further dissect the devised methods and provide an experiment-based hypothesis that reveals the need for improved generalisability to tackle diversity present in multi-centre datasets and routine clinical procedures.
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| 4. |
- Park, Seung Hyun, et al.
(author)
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Nonpharmaceutical interventions reduce the incidence and mortality of COVID-19: A study based on the survey from the International COVID-19 Research Network (ICRN)
- 2023
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In: Journal of Medical Virology. - : WILEY. - 0146-6615 .- 1096-9071. ; 95:2
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Journal article (peer-reviewed)abstract
- The recently emerged novel coronavirus, "severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2)," caused a highly contagious disease called coronavirus disease 2019 (COVID-19). It has severely damaged the worlds most developed countries and has turned into a major threat for low- and middle-income countries. Since its emergence in late 2019, medical interventions have been substantial, and most countries relied on public health measures collectively known as nonpharmaceutical interventions (NPIs). We aimed to centralize the accumulative knowledge of NPIs against COVID-19 for each country under one worldwide consortium. International COVID-19 Research Network collaborators developed a cross-sectional online survey to assess the implications of NPIs and sanitary supply on the incidence and mortality of COVID-19. The survey was conducted between January 1 and February 1, 2021, and participants from 92 countries/territories completed it. The association between NPIs, sanitation supplies, and incidence and mortality were examined by multivariate regression, with the log-transformed value of population as an offset value. The majority of countries/territories applied several preventive strategies, including social distancing (100.0%), quarantine (100.0%), isolation (98.9%), and school closure (97.8%). Individual-level preventive measures such as personal hygiene (100.0%) and wearing facial masks (94.6% at hospitals; 93.5% at mass transportation; 91.3% in mass gathering facilities) were also frequently applied. Quarantine at a designated place was negatively associated with incidence and mortality compared to home quarantine. Isolation at a designated place was also associated with reduced mortality compared to home isolation. Recommendations to use sanitizer for personal hygiene reduced incidence compared to the recommendation to use soap. Deprivation of masks was associated with increased incidence. Higher incidence and mortality were found in countries/territories with higher economic levels. Mask deprivation was pervasive regardless of economic level. NPIs against COVID-19 such as using sanitizer, quarantine, and isolation can decrease the incidence and mortality of COVID-19.
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