数据驱动的生殖健康:生物信息学和机器学习方法的角色
This book provides insight into the transformative impact of data-driven approaches on reproductive health. Chapters cover a wealth of intricate algorithms of genomic analysis, predictive modeling, and personalized treatment strategies, providing an up-to-date view of the reproductive healthcare landscape. With more than 20 code-based examples, the book decodes complex biological data using bioinformatics and machine learning and provides valuable insights into fertility, genetic disorders, and personalized medicine. This book is relevant for healthcare professionals, researchers, and students in the fields of reproductive medicine, bioinformatics, and genetics.
这本书提供了关于基于数据的方法对生殖健康产生 transformative 影响的见解。各章节涵盖了一系列复杂的基因分析算法、预测建模和个性化治疗策略,提供了一个最新的生殖医疗景观视图。该书包含超过 20 个基于代码的例子,使用生物信息学和机器学习解码复杂生物学数据,并为生育能力、遗传疾病和个人化医学提供了有价值的见解。 这本书对生殖医学、生物信息学以及基因领域的医疗专业人士、研究人员和学生来说都具有相关性。
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