Large language model (ChatGPT) as a support tool for breast tumor board

Abstract Large language models (LLM) such as ChatGPT have gained public and scientific attention. The aim of this study is to evaluate ChatGPT as a support tool for breast tumor board decisions making. We inserted into ChatGPT-3.5 clinical information of ten consecutive patients presented in a breast tumor board in our institution. We asked the chatbot to recommend management. The results generated by ChatGPT were compared to the final recommendations of the tumor board. They were also graded independently by two senior radiologists. Grading scores were between 1–5 (1 = completely disagree, 5 = completely agree), and in three different categories: summarization, recommendation, and explanation. The mean age was 49.4, 8/10 (80%) of patients had invasive ductal carcinoma, one patient (1/10, 10%) had a ductal carcinoma in-situ and one patient (1/10, 10%) had a phyllodes tumor with atypia. In seven out of ten cases (70%), ChatGPT’s recommendations were similar to the tumor board’s decisions. Mean scores while grading the chatbot’s summarization, recommendation and explanation by the first reviewer were 3.7, 4.3, and 4.6 respectively. Mean values for the second reviewer were 4.3, 4.0, and 4.3, respectively. In this proof-of-concept study, we present initial results on the use of an LLM as a decision support tool in a breast tumor board. Given the significant advancements, it is warranted for clinicians to be familiar with the potential benefits and harms of the technology

Alkaliphiles : The Emerging Biological Tools Enhancing Concrete Durability

Concrete is one of the most commonly used building materials ever used. Despite it is a very important and common construction material, concrete is very sensitive to crack formation and requires repair. A variety of chemical-based techniques and materials have been developed to repair concrete cracks. Although the use of these chemical-based repair systems are the best commercially available choices, there have also been concerns related to their use. These repair agents suffer from inefficiency and unsustainability. Most of the products are expensive and susceptible to degradation, exhibit poor bonding to the cracked concrete surfaces, and are characterized by different physical properties such as thermal expansion coefficients which are different to that of concrete. Moreover, many of these repair agents contain chemicals that pose environmental and health hazards. Thus, there has been interest in developing concrete crack repair agents that are efficient, long lasting, safe, and benign to the environment and exhibit physical properties which resemble that of the concrete. The search initiated by these desires brought the use of biomineralization processes as tools in mending concrete cracks. Among biomineralization processes, microbially initiated calcite precipitation has emerged as an interesting alternative to the existing chemical-based concrete crack repairing system. Indeed, results of several studies on the use of microbial-based concrete repair agents revealed the remarkable potential of this approach in the fight against concrete deterioration. In addition to repairing existing concrete cracks, microorganisms have also been considered to make protective surface coating (biodeposition) on concrete structures and in making self-healing concrete. Even though a wide variety of microorganisms can precipitate calcite, the nature of concrete determines their applicability. One of the important factors that determine the applicability of microbes in concrete is pH. Concrete is highly alkaline in nature, and hence the microbes envisioned for this application are alkaliphilic or alkali-tolerant. This work reviews the available information on applications of microbes in concrete: repairing existing cracks, biodeposition, and self-healing. Moreover, an effort is made to discuss biomineralization processes that are relevant to extend the durability of concrete structures