Improving Patient Pre-screening for Clinical Trials: Assisting Physicians with Large Language Models

Physicians considering clinical trials for their patients are met with the laborious process of checking many text based eligibility criteria. Large Language Models (LLMs) have shown to perform well for clinical information extraction and clinical reasoning, including medical tests, but not yet in real-world scenarios. This paper investigates the use of InstructGPT to assist physicians in determining eligibility for clinical trials based on a patient's summarised medical profile. Using a prompting strategy combining one-shot, selection-inference and chain-of-thought techniques, we investigate the performance of LLMs on 10 synthetically created patient profiles. Performance is evaluated at four levels: ability to identify screenable eligibility criteria from a trial given a medical profile; ability to classify for each individual criterion whether the patient qualifies; the overall classification whether a patient is eligible for a clinical trial and the percentage of criteria to be screened by physician. We evaluated against 146 clinical trials and a total of 4,135 eligibility criteria. The LLM was able to correctly identify the screenability of 72% (2,994/4,135) of the criteria. Additionally, 72% (341/471) of the screenable criteria were evaluated correctly. The resulting trial level classification as eligible or ineligible resulted in a recall of 0.5. By leveraging LLMs with a physician-in-the-loop, a recall of 1.0 and precision of 0.71 on clinical trial level can be achieved while reducing the amount of criteria to be checked by an estimated 90%. LLMs can be used to assist physicians with pre-screening of patients for clinical trials. By forcing instruction-tuned LLMs to produce chain-of-thought responses, the reasoning can be made transparent to and the decision process becomes amenable by physicians, thereby making such a system feasible for use in real-world scenarios.Comment: 11 pages, 4 tables, 2 figure

Azimuthal di-hadron correlations in d+Au and Au+Au collisions at sNN=200\sqrt{s_{NN}}=200 GeV from STAR

Yields, correlation shapes, and mean transverse momenta \pt{} of charged particles associated with intermediate to high-\pt{} trigger particles (2.5 < \pt < 10 \GeVc) in d+Au and Au+Au collisions at \snn=200 GeV are presented. For associated particles at higher \pt \gtrsim 2.5 \GeVc, narrow correlation peaks are seen in d+Au and Au+Au, indicating that the main production mechanism is jet fragmentation. At lower associated particle \pt < 2 \GeVc, a large enhancement of the near- (\dphi \sim 0) and away-side (\dphi \sim \pi) associated yields is found, together with a strong broadening of the away-side azimuthal distributions in Au+Au collisions compared to d+Au measurements, suggesting that other particle production mechanisms play a role. This is further supported by the observed significant softening of the away-side associated particle yield distribution at \dphi \sim \pi in central Au+Au collisions.Comment: 16 pages, 11 figures, updated after journal revie

Impact of COVID-19 on cardiovascular testing in the United States versus the rest of the world

Objectives: This study sought to quantify and compare the decline in volumes of cardiovascular procedures between the United States and non-US institutions during the early phase of the coronavirus disease-2019 (COVID-19) pandemic. Background: The COVID-19 pandemic has disrupted the care of many non-COVID-19 illnesses. Reductions in diagnostic cardiovascular testing around the world have led to concerns over the implications of reduced testing for cardiovascular disease (CVD) morbidity and mortality. Methods: Data were submitted to the INCAPS-COVID (International Atomic Energy Agency Non-Invasive Cardiology Protocols Study of COVID-19), a multinational registry comprising 909 institutions in 108 countries (including 155 facilities in 40 U.S. states), assessing the impact of the COVID-19 pandemic on volumes of diagnostic cardiovascular procedures. Data were obtained for April 2020 and compared with volumes of baseline procedures from March 2019. We compared laboratory characteristics, practices, and procedure volumes between U.S. and non-U.S. facilities and between U.S. geographic regions and identified factors associated with volume reduction in the United States. Results: Reductions in the volumes of procedures in the United States were similar to those in non-U.S. facilities (68% vs. 63%, respectively; p = 0.237), although U.S. facilities reported greater reductions in invasive coronary angiography (69% vs. 53%, respectively; p < 0.001). Significantly more U.S. facilities reported increased use of telehealth and patient screening measures than non-U.S. facilities, such as temperature checks, symptom screenings, and COVID-19 testing. Reductions in volumes of procedures differed between U.S. regions, with larger declines observed in the Northeast (76%) and Midwest (74%) than in the South (62%) and West (44%). Prevalence of COVID-19, staff redeployments, outpatient centers, and urban centers were associated with greater reductions in volume in U.S. facilities in a multivariable analysis. Conclusions: We observed marked reductions in U.S. cardiovascular testing in the early phase of the pandemic and significant variability between U.S. regions. The association between reductions of volumes and COVID-19 prevalence in the United States highlighted the need for proactive efforts to maintain access to cardiovascular testing in areas most affected by outbreaks of COVID-19 infection

The ALICE experiment at the CERN LHC

ALICE (A Large Ion Collider Experiment) is a general-purpose, heavy-ion detector at the CERN LHC which focuses on QCD, the strong-interaction sector of the Standard Model. It is designed to address the physics of strongly interacting matter and the quark-gluon plasma at extreme values of energy density and temperature in nucleus-nucleus collisions. Besides running with Pb ions, the physics programme includes collisions with lighter ions, lower energy running and dedicated proton-nucleus runs. ALICE will also take data with proton beams at the top LHC energy to collect reference data for the heavy-ion programme and to address several QCD topics for which ALICE is complementary to the other LHC detectors. The ALICE detector has been built by a collaboration including currently over 1000 physicists and engineers from 105 Institutes in 30 countries. Its overall dimensions are 161626 m3 with a total weight of approximately 10 000 t. The experiment consists of 18 different detector systems each with its own specific technology choice and design constraints, driven both by the physics requirements and the experimental conditions expected at LHC. The most stringent design constraint is to cope with the extreme particle multiplicity anticipated in central Pb-Pb collisions. The different subsystems were optimized to provide high-momentum resolution as well as excellent Particle Identification (PID) over a broad range in momentum, up to the highest multiplicities predicted for LHC. This will allow for comprehensive studies of hadrons, electrons, muons, and photons produced in the collision of heavy nuclei. Most detector systems are scheduled to be installed and ready for data taking by mid-2008 when the LHC is scheduled to start operation, with the exception of parts of the Photon Spectrometer (PHOS), Transition Radiation Detector (TRD) and Electro Magnetic Calorimeter (EMCal). These detectors will be completed for the high-luminosity ion run expected in 2010. This paper describes in detail the detector components as installed for the first data taking in the summer of 2008

Laser ablation with copper vapour lasers

The use of copper vapour lasers for laser ablation in laser materials processing applications is studied. To this purpose, the generation of near diffraction-limited beam quality output from a single medium-scale oscillator is demonstrated via matching the total buffer gas pressure to the specific electrical input power loading and the degree of insulation of the plasma tube. The design and characterisation of a Master-Oscillator Power-Amplifier system based on a smallbore oscillator is also described, focusing on pulse stretching techniques to provide efficient seeding required for producing 20-50 W high beam-quality output for laser materials processing purposes. Various experimental studies on the fundamental processes of laser ablation of metals are presented. The effect of the background gas properties on shock-wave formation in laser generated plasmas is studied using a ballistic pendulum. The experimental findings are found to be accurately described by a modified Sedov-Taylor-Von Neumann theory which accounts for the effect of the piston-mass. The theory is applied to characterise the fluorination process in the shock-wave, in view of oxygen isotope analysis in geochemistry. Atomic emission spectroscopy is shown to provide some measure of the electron temperature and electron density at the plasma core. The experimental results are discussed in view of existing models to describe the extreme Stark-broadening and self-absorption in dense, cool plasmas. A comparative study of the use of femtosecond and nanosecond pulsed lasers for laser ablation of metals is presented to assess the relative importance of thermal diffusion. Measurement of the recoil momentum due to ejection of molten particulates during ablation in vacuum provides insight into the effect of material properties. Diffusion-limited surface texturing of metals via direct transfer of an optical interference patterns is demonstrated

Laser ablation with copper vapour lasers

The use of copper vapour lasers for laser ablation in laser materials processing applications is studied. To this purpose, the generation of near diffraction-limited beam quality output from a single medium-scale oscillator is demonstrated via matching the total buffer gas pressure to the specific electrical input power loading and the degree of insulation of the plasma tube. The design and characterisation of a Master-Oscillator Power-Amplifier system based on a smallbore oscillator is also described, focusing on pulse stretching techniques to provide efficient seeding required for producing 20-50 W high beam-quality output for laser materials processing purposes. Various experimental studies on the fundamental processes of laser ablation of metals are presented. The effect of the background gas properties on shock-wave formation in laser generated plasmas is studied using a ballistic pendulum. The experimental findings are found to be accurately described by a modified Sedov-Taylor-Von Neumann theory which accounts for the effect of the piston-mass. The theory is applied to characterise the fluorination process in the shock-wave, in view of oxygen isotope analysis in geochemistry. Atomic emission spectroscopy is shown to provide some measure of the electron temperature and electron density at the plasma core. The experimental results are discussed in view of existing models to describe the extreme Stark-broadening and self-absorption in dense, cool plasmas. A comparative study of the use of femtosecond and nanosecond pulsed lasers for laser ablation of metals is presented to assess the relative importance of thermal diffusion. Measurement of the recoil momentum due to ejection of molten particulates during ablation in vacuum provides insight into the effect of material properties. Diffusion-limited surface texturing of metals via direct transfer of an optical interference patterns is demonstrated.</p

UV laser ablation and irm-GCMS microanalysis of ¹⁸O/¹⁶O and ¹⁷O/¹⁶O with application to a calcium-aluminium-rich inclusion from the Allende meteorite

Analyses of ¹⁸O/¹⁶O and ¹⁷O/¹⁶O in silicate and oxide minerals by UV laser ablation of 100 × 80 × 50 μm sample pits combined with irm-GCMS yield precision and accuracy similar to that of conventional methods. This represents a 100-fold reduction in minimum size relative to other fluorination methods based on gas-source mass spectrometry and enables high-precision in-situ intracrystalline analysis of silicate minerals. Analyses of almandine, forsterite, and schorl of known isotopic compositions indicate an analytical precision of ±0.3‰ (1σ) in δ¹⁸O and ±0.4 in δ¹⁷O with an accuracy of similar magnitude. Application to meteoritic samples is demonstrated by in-situ analysis of pyroxene and melilite from a type B CAI inclusion from the Allende meteorite. The CAI data adhere to the carbonaceous chondrite anhydrous mineral line defined by conventional macroscopic fluorination methods and demonstrate that non-mass dependent differences of 1‰ amu⁻¹ are discernible. The unique combination of analytical and spatial resolution afforded by the new UV laser microprobe will allow high-precision mapping of the distribution of anomalous oxygen in minerals from calcium-aluminum-rich inclusions on a previously unattainable scale.8 page(s

Privacy Enhancing Technologies Whitepaper:Developed by Centre of Excellence – Data Sharing and Cloud

This whitepaper provides decision-makers with insights on the benefits of Privacy Enhancing Technologies (PETs) for data collaborations. With recent growth and development of data sharing, public and private organisations can realise new economic and societal value potential. However, data collaboration participants often face barriers for data sharing in form of privacy, commercial and reputational risks. PETs can play a role for reducing these barriers and increasing trust in data collaborations where data cannot be shared directly, since PETs allow to generate insights without disclosing the underlying data. The paper focuses on the most important PETs and their benefits for respective use cases. It also covers challenges that need to be overcome for large-scale adoption of PETs and lastly, shows tangible steps for fostering implementation of these technologies in organisations

Analytical Problem Solving Based on Causal, Correlational and Deductive Models

Many approaches for solving problems in business and industry are based on analytics and statistical modeling. Analytical problem solving is driven by the modeling of relationships between dependent (Y) and independent (X) variables, and we discuss three frameworks for modeling such relationships: cause-and-effect modeling, popular in applied statistics and beyond, correlational predictive modeling, popular in machine learning, and deductive (first-principles) modeling, popular in business analytics and operations research. We aim to explain the differences between these types of models, and flesh out the implications of these differences for study design, for discovering potential X/Y relationships, and for the types of solution patterns that each type of modeling could support. We use our account to clarify the popular descriptive-diagnostic-predictive-prescriptive analytics framework, but extend it to offer a more complete model of the process of analytical problem solving, reflecting the essential differences between causal, correlational, and deductive models

Exploring the explosive ablation regime of metals in nanosecond micromachining

We present results of single shot ablation experiments for a variety of metal samples (In, Al, Cu, Mo, W, Ti) using visible, nanosecond lasers at fluences up to approximately 10⁴ J cm⁻². At low fluences, usually less than 10² J cm⁻², small amounts of material were removed and removal was approximately uniform across the ablation crater. As the fluence increased above approximately 10² J cm⁻², substantially more material was removed and a conical pit developed in the center of the ablation crater. The appearance of these conical pits is consistent with material removed by phase explosion mechanisms. In this paper, this ablation phenomenon will be investigated by presenting the crater morphology as a function of fluence. Consequences for micromachining with visible, high repetition rate, nanosecond lasers will be discussed.8 page(s