A deep learning model for predicting blastocyst formation from cleavage-stage human embryos using time-lapse images.

Efficient prediction of blastocyst formation from early-stage human embryos is imperative for improving the success rates of assisted reproductive technology (ART). Clinics transfer embryos at the blastocyst stage on Day-5 but Day-3 embryo transfer offers the advantage of a shorter culture duration, which reduces exposure to laboratory conditions, potentially enhancing embryonic development within a more conducive uterine environment and improving the likelihood of successful pregnancies. In this paper, we present a novel ResNet-GRU deep-learning model to predict blastocyst formation at 72 HPI.

Variations of generalized weak contractions in partially ordered b-metric space.

Objectives: This paper explored the fixed point results for the mappings satisfying generalized weak contractive conditions in a complete partially ordered b-metric space. These contractions are some variations of the work done by the authors (Mituku et al. in BMC Res Notes 13:537.

Fixed point results of weakly contraction mappings in partially ordered b-metric spaces.

Objectives: We explored the results of fixed point, coincidence point and coupled coincidence point for the mappings in an ordered metric spaces. Our results generalized and extended the well-known results in the literature. Some numerical examples are provided for justifying the results obtained.

Generalized fixed point results of rational type contractions in partially ordered metric spaces.

Objectives: We investigated the existence and uniqueness of a fixed point for the mapping satisfying generalized rational type contraction conditions in metric space endowed with partial order. Suitable examples are presented to justify the results obtained.

Result: Some new fixed point results have been obtained for a mapping fulfilling generalized contractions.