Deep Learning Models for Predicting Malignancy Risk in CT-Detected Pulmonary Nodules: A Systematic Review and Meta-analysis.

Background: There has been growing interest in using artificial intelligence/deep learning (DL) to help diagnose prevalent diseases earlier. In this study we sought to survey the landscape of externally validated DL-based computer-aided diagnostic (CADx) models, and assess their diagnostic performance for predicting the risk of malignancy in computed tomography (CT)-detected pulmonary nodules.

Methods: An electronic search was performed in four databases (from inception to 10 August 2023).

Enhancing the quality and safety of Nocellara del Belice green table olives produced using the Castelvetrano method.

The Castelvetrano method is the most widely used among the various table olive processing styles in Sicily. After debittering, the product is stored at low temperatures to prevent the growth of undesirable microorganisms. In an effort to enhance the production process, yeast isolates underwent genotypic characterization and technological screening.

Effect of reproductive management programs that prioritized artificial insemination at detected estrus or timed artificial insemination on the economic performance of primiparous Holstein cows of different genetic merit for fertility.

The objective of this randomized controlled experiment was to evaluate the effect of reproductive management programs that prioritized artificial insemination (AI) at detected estrus (AIE) or timed AI (TAI) during the first lactation on the economic performance of dairy cows of different genomically enhanced predicted transmitting ability for fertility. Lactating primiparous Holstein cows from 6 commercial farms were stratified into high, medium, and low fertility groups based on a reproduction index value calculated from multiple genomically enhanced predicted transmitting abilities to predict the number of days to achieve pregnancy. Within herd and fertility group, cows were randomly assigned either to a program that prioritized AIE (P-AIE; n = 1,416) and used TAI for cows not AIE for all AI services or another that prioritized TAI and had an extended voluntary waiting period for first service and prioritized TAI for second and greater AI services (P-TAI; n = 1,338).

Effect of reproductive management programs that prioritized artificial insemination at detected estrus or timed artificial insemination on the reproductive performance of primiparous Holstein cows of different genetic merit for fertility.

Our objective was to compare reproductive outcomes of primiparous lactating Holstein cows of different genetic merit for fertility submitted for insemination with management programs that prioritized artificial insemination (AI) at detected estrus (AIE) or timed AI (TAI). Moreover, we aimed to determine whether subgroups of cows with different fertility potential would present a distinct response to the reproductive management strategies compared. Lactating primiparous Holstein cows (n = 6 commercial farms) were stratified into high (Hi-Fert), medium (Med-Fert), and low (Lo-Fert) genetic fertility groups (FG) based on a Reproduction Index value calculated from multiple genomic-enhanced predicted transmitting abilities.

Effect of Genetic and Environmental Factors on Twin Pregnancy in Primiparous Dairy Cows.

Twin pregnancies are highly undesirable in dairy cattle; they compromise the health and wellbeing of a cow and dramatically impair the farm economy. Recently, a genomic prediction for twin pregnancies has been developed. The objective of this study was to assess environmental and management risk factors affecting the incidence of twin pregnancies in high-producing dairy cows in their first lactation, with a special emphasis placed on the genomic prediction values of twin pregnancy.