Abstract: Importance Mammography screening currently relies on subjective human interpretation. Artificial intelligence (AI) advances could be used to increase mammography screening accuracy by reducing missed cancers and false positives. Objective To evaluate whether AI can overcome human mammography interpretation limitations with a rigorous, unbiased evaluation of machine learning algorithms. Design, Setting, and Participants In this diagnostic accuracy study conducted between September 2016 and November 2017, an international, crowdsourced challenge was hosted to foster AI algorithm development focused on interpreting screening mammography. More than 1100 participants comprising 126 teams from 44 countries participated. Analysis began November 18, 2016. Main Outcomes and Measurements Algorithms used images alone (challenge 1) or combined images, previous examinations (if available), and clinical and demographic risk factor data (challenge 2) and output a score that translated to cancer yes/no within 12 months. Algorithm accuracy for breast cancer detection was evaluated using area under the curve and algorithm specificity compared with radiologists' specificity with radiologists' sensitivity set at 85.9% (United States) and 83.9% (Sweden). An ensemble method aggregating top-performing AI algorithms and radiologists' recall assessment was developed and evaluated. Results Overall, 144231 screening mammograms from 85580 US women (952 cancer positive <= 12 months from screening) were used for algorithm training and validation. A second independent validation cohort included 166578 examinations from 68008 Swedish women (780 cancer positive). The top-performing algorithm achieved an area under the curve of 0.858 (United States) and 0.903 (Sweden) and 66.2% (United States) and 81.2% (Sweden) specificity at the radiologists' sensitivity, lower than community-practice radiologists' specificity of 90.5% (United States) and 98.5% (Sweden). Combining top-performing algorithms and US radiologist assessments resulted in a higher area under the curve of 0.942 and achieved a significantly improved specificity (92.0%) at the same sensitivity. Conclusions and Relevance While no single AI algorithm outperformed radiologists, an ensemble of AI algorithms combined with radiologist assessment in a single-reader screening environment improved overall accuracy. This study underscores the potential of using machine learning methods for enhancing mammography screening interpretation. Question How do deep learning algorithms perform compared with radiologists in screening mammography interpretation? Findings In this diagnostic accuracy study using 144231 screening mammograms from 85580 women from the United States and 166578 screening mammograms from 68008 women from Sweden, no single artificial intelligence algorithm outperformed US community radiologist benchmarks; including clinical data and prior mammograms did not improve artificial intelligence performance. However, combining best-performing artificial intelligence algorithms with single-radiologist assessment demonstrated increased specificity. Meaning Integrating artificial intelligence to mammography interpretation in single-radiologist settings could yield significant performance improvements, with the potential to reduce health care system expenditures and address resource scarcity experienced in population-based screening programs. This diagnostic accuracy study evaluates whether artificial intelligence can overcome human mammography interpretation limits with a rigorous, unbiased evaluation of machine learning algorithms.

Abstract: The first observation of the semileptonic b-baryon decay Lambda(0)(b) -> Lambda(+)(c) tau(-)(nu) over bar (tau) with a significance of 6.1 sigma, is reported using a data sample corresponding to 3 fb(-1) of integrated luminosity, collected by the LHCb experiment at center-of-mass energies of 7 and 8 TeV at the LHC. The tau(-) lepton is reconstructed in the hadronic decay to three charged pions. The ratio K = B(Lambda(0)(b) -> Lambda(+)(c) tau(-)(nu) over bar (tau))/B(Lambda(0)(b) -> Lambda(+)(c)pi(-)pi(+)pi(-)) is measured to be 2.46 +/- 0.27 +/- 0.40, where the first uncertainty is statistical and the second systematic. The branching fraction B(Lambda(0)(b) -> Lambda(+)(c) tau(-)(nu) over bar (tau)) (1.50 +/- 0.16 +/- 0.25 +/- 0.23)% is obtained, where the third uncertainty is from the external branching fraction of the normalization channel Lambda(0)(b) -> Lambda(+)(c)pi(-)pi(+)pi(-). The ratio of semileptonic branching fractions R(Lambda(+)(c)) B(Lambda(0)(b) -> Lambda(+)(c) tau(-)(nu) over bar (tau))/B(Lambda(0)(b) -> Lambda(+)(c)mu(-)(nu) over bar (tau)) is derived to be 0.242 +/- 0.026 +/- 0.040 +/- 0.059, where the external branching fraction uncertainty from the channel Lambda(0)(b) -> Lambda(+)(c)mu(-)(nu) over bar (tau) contributes to the last term. This result is in agreement with the standard model prediction.

Abstract: This Letter reports the observation of single top quarks produced together with a photon, which directly probes the electroweak coupling of the top quark. The analysis uses 139 fb(-1) of 13 TeV proton-proton collision data collected with the ATLAS detector at the Large Hadron Collider. Requiring a photon with transverse momentum larger than 20 GeV and within the detector acceptance, the fiducial cross section is measured to be 688 +/- 23(stat)(-71)(+75) (syst) fb, to be compared with the standard model prediction of 515(-42)(+36) fb at next-to-leading order in QCD.

Abstract: We present a novel mode of neutrinoless double-beta decay with emission of a light Majoron-like scalar particle phi. We assume it couples via an effective seven-dimensional operator with a (V + A) lepton current and (V +/- A) quark currents leading to a long-range contribution that is unsuppressed by the light neutrino mass. We calculate the total double-beta decay rate and determine the fully differential shape for this mode. We find that future double-beta decay searches are sensitive to scales of the order Lambda(NP) approximate to 1 TeV for the effective operator and a light scalar m(phi) < 0.2 MeV, based on ordinary double-beta decay Majoron searches. The angular and energy distributions can deviate considerably from that of two-neutrino double-beta decay, which is the main background. We point out possible ultraviolet completions where such an effective operator can emerge.

Abstract: The optical appearance of a body compact enough to feature an unstable bound orbit, when surrounded by an accretion disk, is expected to be dominated by a luminous ring of radiation enclosing a central brightness depression typically known as the shadow. Despite observational limitations, the rough details of this picture have been now confirmed by the results of the Event Horizon Telescope (EHT) Collaboration on the imaging of the M87 and Milky Way supermassive central objects. However, the precise characterization of both features-ring and shadow-depends on the interaction between the background geometry and the accretion disk, thus being a fertile playground to test our theories on the nature of compact objects and the gravitational field itself in the strong-field regime. In this work we use both features in order to test a continuous family of solutions interpolating between regular black holes and horizonless compact objects, which arise within the Eddington-inspired Born-Infeld theory of gravity, a viable extension of Einstein's general relativity (GR). To this end we consider seven distinctive classes of such configurations (five black holes and two traversable wormholes) and study their optical appearances under illumination by a geometrically and optically thin accretion disk, emitting monochromatically with three analytic intensity profiles previously suggested in the literature. We build such images and consider the sub-ring structure created by light rays crossing the disk more than once and existing on top of the main ring of radiation. We discuss in detail the modifications as compared to their GR counterparts, the Lyapunov exponents of unstable nearly-bound orbits, as well as the differences between black hole and traversable wormholes for the three intensity profiles. In addition we use the claim by the EHT Collaboration on the radius of the bright ring acting (under proper calibrations) as a proxy for the radius of the shadow itself to explore the parameter space of our solutions compatible with such a result.