Recent studies have introduced attention models for medical visual question answering (MVQA). In medical research, not only is the modeling of “visual attention” crucial, but the modeling of “question attention” is equally significant. To facilitate bidirectional reasoning in the attention processes involving medical images and questions, a new MVQA architecture, named MCAN, has been proposed. This architecture incorporated a cross-modal co-attention network, FCAF, which identifies key words in questions and principal parts in images. Through a meta-learning channel attention module (MLCA), weights were adaptively assigned to each word and region, reflecting the model’s focus on specific words and regions during reasoning. Additionally, this study specially designed and developed a medical domain-specific word embedding model, Med-GloVe, to further enhance the model’s accuracy and practical value. Experimental results indicated that MCAN proposed in this study improved the accuracy by 7.7% on free-form questions in the Path-VQA dataset, and by 4.4% on closed-form questions in the VQA-RAD dataset, which effectively improves the accuracy of the medical vision question answer.
Objective To assess the efficacy and safety of neoadjuvant intraarterial chemotherapy in the treatment of advanced cervical cancer. Methods We searched databases including PubMed, EMbase, The Cochrane Library, VIP, CNKI, CBMdisc, conference articles, and Ongoing Controlled Trial for Random Controlled Trials and quasi-Random Controlled Trials up to October 2009. For homogeneous studies, we performed meta-analysis. Results Fifteen studies involving 1 331 participants with advanced cervical cancer were included. Twelve studies showed that the efficacy of the NIC group was 6.72 times than that of the traditional group. Several studies showed that the survival rate of the NIC group was better than that of the traditional group. Meanwhile, the adverse events of the NIC group were fewer than those of the traditional group. Conclusions The results of this system review show that, NIC which is more effective than conventional treatments with less adverse reactions provides a new adjunct for clinical treatment of advanced cervical cancer . However, due to the current clinical treatment for the disease is the coexistence of multiple chemotherapy program status, the higher quality and more focused clinical research which will compare NIC with a variety of conventional chemotherapy are needed in the further.