Estimating the quality of prediction tools.

2022 ◽  
pp. 325-352
Author(s):  
R. Karl Hanson
Keyword(s):  
Prediction Tools

scholarly journals Conventional risk prediction models fail to accurately predict mortality risk among patients with coronavirus disease 2019 in intensive care units: a difficult time to assess clinical severity and quality of care

2021 ◽  
Vol 9 (1) ◽  
Author(s):  
Hideki Endo ◽  
Hiroyuki Ohbe ◽  
Junji Kumasawa ◽  
Shigehiko Uchino ◽  
Satoru Hashimoto ◽  
...  
Keyword(s):  
Intensive Care ◽  
Intensive Care Units ◽  
Risk Prediction ◽  
Prediction Models ◽  
Clinical Severity ◽  
Risk Prediction Models ◽  
Prediction Tools ◽  
Difficult Time ◽  
Care Database

AbstractSince the start of the coronavirus disease 2019 (COVID-19) pandemic, it has remained unknown whether conventional risk prediction tools used in intensive care units are applicable to patients with COVID-19. Therefore, we assessed the performance of established risk prediction models using the Japanese Intensive Care database. Discrimination and calibration of the models were poor. Revised risk prediction models are needed to assess the clinical severity of COVID-19 patients and monitor healthcare quality in ICUs overwhelmed by patients with COVID-19.

scholarly journals Clinical impact and quality of randomized controlled trials involving interventions evaluating artificial intelligence prediction tools: a systematic review

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Qian Zhou ◽  
Zhi-hang Chen ◽  
Yi-heng Cao ◽  
Sui Peng
Keyword(s):  
Artificial Intelligence ◽  
Systematic Review ◽  
Randomized Controlled Trials ◽  
Model Development ◽  
Clinical Impact ◽  
Controlled Trials ◽  
Prediction Tools ◽  
Randomized Controlled ◽  
The Impact

AbstractThe evidence of the impact of traditional statistical (TS) and artificial intelligence (AI) tool interventions in clinical practice was limited. This study aimed to investigate the clinical impact and quality of randomized controlled trials (RCTs) involving interventions evaluating TS, machine learning (ML), and deep learning (DL) prediction tools. A systematic review on PubMed was conducted to identify RCTs involving TS/ML/DL tool interventions in the past decade. A total of 65 RCTs from 26,082 records were included. A majority of them had model development studies and generally good performance was achieved. The function of TS and ML tools in the RCTs mainly included assistive treatment decisions, assistive diagnosis, and risk stratification, but DL trials were only conducted for assistive diagnosis. Nearly two-fifths of the trial interventions showed no clinical benefit compared to standard care. Though DL and ML interventions achieved higher rates of positive results than TS in the RCTs, in trials with low risk of bias (17/65) the advantage of DL to TS was reduced while the advantage of ML to TS disappeared. The current applications of DL were not yet fully spread performed in medicine. It is predictable that DL will integrate more complex clinical problems than ML and TS tools in the future. Therefore, rigorous studies are required before the clinical application of these tools.

scholarly journals Modeling COVID-19: Forecasting and analyzing the dynamics of the outbreak in Hubei and Turkey

2020 ◽  
Author(s):  
Ibrahim Halil Aslan ◽  
Mahir Demir ◽  
Michael Morgan Wise ◽  
Suzanne Lenhart
Keyword(s):  
Coupled System ◽  
Global Perspective ◽  
Basic Reproductive Number ◽  
Reproductive Number ◽  
Quality Of Data ◽  
Local Data ◽  
Social Distancing ◽  
Prediction Tools ◽  
High Level

AbstractAs the pandemic of Coronavirus Disease 2019 (COVID-19) rages throughout the world, accurate modeling of the dynamics thereof is essential. However, since the availability and quality of data varies dramatically from region to region, accurate modeling directly from a global perspective is difficult, if not altogether impossible. Nevertheless, via local data collected by certain regions, it is possible to develop accurate local prediction tools, which may be coupled to develop global models.In this study, we analyze the dynamics of local outbreaks of COVID-19 via a coupled system of ordinary differential equations (ODEs). Utilizing the large amount of data available from the ebbing outbreak in Hubei, China as a testbed, we estimate the basic reproductive number, ℛ0 of COVID-19 and predict the total cases, total deaths, and other features of the Hubei outbreak with a high level of accuracy. Through numerical experiments, we observe the effects of quarantine, social distancing, and COVID-19 testing on the dynamics of the outbreak. Using knowledge gleaned from the Hubei outbreak, we apply our model to analyze the dynamics of outbreak in Turkey. We provide forecasts for the peak of the outbreak and the total number of cases/deaths in Turkey, for varying levels of social distancing, quarantine, and COVID-19 testing.

Immunoferritin localization of intracellular antigens in positively stained frozen sections

1978 ◽  
Vol 36 (2) ◽  
pp. 168-169
Author(s):  
K. T. Tokuyasu
Keyword(s):  
Surface Tension ◽  
Water Surface ◽  
Thin Layers ◽  
The Other ◽  
Positive Staining ◽  
Frozen Sections ◽  
The Past ◽  
Ultrathin Frozen Sections ◽  
Definition Of

During the past investigations of immunoferritin localization of intracellular antigens in ultrathin frozen sections, we found that the degree of negative staining required to delineate u1trastructural details was often too dense for the recognition of ferritin particles. The quality of positive staining of ultrathin frozen sections, on the other hand, has generally been far inferior to that attainable in conventional plastic embedded sections, particularly in the definition of membranes. As we discussed before, a main cause of this difficulty seemed to be the vulnerability of frozen sections to the damaging effects of air-water surface tension at the time of drying of the sections.Indeed, we found that the quality of positive staining is greatly improved when positively stained frozen sections are protected against the effects of surface tension by embedding them in thin layers of mechanically stable materials at the time of drying (unpublished).

Lithography below 100 nm

1983 ◽  
Vol 41 ◽  
pp. 96-99
Author(s):  
L. D. Jackel
Keyword(s):  
Spatial Distribution ◽  
Electron Beam ◽  
Electron Scattering ◽  
Electron Beam Lithography ◽  
Substrate Material ◽  
Local Electron ◽  
Electron Dose ◽  
Positive Resist ◽  
Exposure Process

Most production electron beam lithography systems can pattern minimum features a few tenths of a micron across. Linewidth in these systems is usually limited by the quality of the exposing beam and by electron scattering in the resist and substrate. By using a smaller spot along with exposure techniques that minimize scattering and its effects, laboratory e-beam lithography systems can now make features hundredths of a micron wide on standard substrate material. This talk will outline sane of these high- resolution e-beam lithography techniques.We first consider parameters of the exposure process that limit resolution in organic resists. For concreteness suppose that we have a “positive” resist in which exposing electrons break bonds in the resist molecules thus increasing the exposed resist's solubility in a developer. Ihe attainable resolution is obviously limited by the overall width of the exposing beam, but the spatial distribution of the beam intensity, the beam “profile” , also contributes to the resolution. Depending on the local electron dose, more or less resist bonds are broken resulting in slower or faster dissolution in the developer.

Convergent Beam Electron Diffraction

1978 ◽  
Vol 36 (3) ◽  
pp. 304-315
Author(s):  
G. Lehmpfuhl
Keyword(s):  
Electron Diffraction ◽  
Diffraction Pattern ◽  
Crystal Surface ◽  
Diffraction Spot ◽  
Crystal Thickness ◽  
Large Area ◽  
Electron Microscopic ◽  
Additional Information ◽  
Microscopic Investigations

Introduction In electron microscopic investigations of crystalline specimens the direct observation of the electron diffraction pattern gives additional information about the specimen. The quality of this information depends on the quality of the crystals or the crystal area contributing to the diffraction pattern. By selected area diffraction in a conventional electron microscope, specimen areas as small as 1 µ in diameter can be investigated. It is well known that crystal areas of that size which must be thin enough (in the order of 1000 Å) for electron microscopic investigations are normally somewhat distorted by bending, or they are not homogeneous. Furthermore, the crystal surface is not well defined over such a large area. These are facts which cause reduction of information in the diffraction pattern. The intensity of a diffraction spot, for example, depends on the crystal thickness. If the thickness is not uniform over the investigated area, one observes an averaged intensity, so that the intensity distribution in the diffraction pattern cannot be used for an analysis unless additional information is available.

Observability of Very Thick Specimen by Using Transmission Scanning Electron Microscope

1971 ◽  
Vol 29 ◽  
pp. 26-27
Author(s):  
K. Shibatomi ◽  
T. Yamanoto ◽  
H. Koike
Keyword(s):  
Electron Microscope ◽  
Image Quality ◽  
Scanning Electron Microscope ◽  
Chromatic Aberration ◽  
Image Contrast ◽  
Objective Lens ◽  
Thick Specimen ◽  
Transmission Electron ◽  
Scanning Electron

In the observation of a thick specimen by means of a transmission electron microscope, the intensity of electrons passing through the objective lens aperture is greatly reduced. So that the image is almost invisible. In addition to this fact, it have been reported that a chromatic aberration causes the deterioration of the image contrast rather than that of the resolution. The scanning electron microscope is, however, capable of electrically amplifying the signal of the decreasing intensity, and also free from a chromatic aberration so that the deterioration of the image contrast due to the aberration can be prevented. The electrical improvement of the image quality can be carried out by using the fascionating features of the SEM, that is, the amplification of a weak in-put signal forming the image and the descriminating action of the heigh level signal of the background. This paper reports some of the experimental results about the thickness dependence of the observability and quality of the image in the case of the transmission SEM.

The Current Situation in Chemical Stabilization of Biological Materials

1972 ◽  
Vol 30 ◽  
pp. 132-133
Author(s):  
John H. Luft
Keyword(s):  
Electron Microscopy ◽  
Electron Microscope ◽  
Osmium Tetroxide ◽  
Molecular Level ◽  
Cross Linking ◽  
Chemical Stabilization ◽  
Specimen Preparation ◽  
Sufficient Condition ◽  
Radio Telescopes

With information processing devices such as radio telescopes, microscopes or hi-fi systems, the quality of the output often is limited by distortion or noise introduced at the input stage of the device. This analogy can be extended usefully to specimen preparation for the electron microscope; fixation, which initiates the processing sequence, is the single most important step and, unfortunately, is the least well understood. Although there is an abundance of fixation mixtures recommended in the light microscopy literature, osmium tetroxide and glutaraldehyde are favored for electron microscopy. These fixatives react vigorously with proteins at the molecular level. There is clear evidence for the cross-linking of proteins both by osmium tetroxide and glutaraldehyde and cross-linking may be a necessary if not sufficient condition to define fixatives as a class.

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