Valter Longo教授,本身是義大利人,到美國求學,本來想成為音樂人,但陰錯陽差鑽入了生化領域,這篇訪談文章Interview with Professor Valter Longo,可以以覽他過去的走的路,其實從某一方面講,蠻特立獨行的,最令我有興趣的是,他還成立組織,販售一種FMD(Fasting Mimic Diet),藉由特殊的營養組成,來模仿身體飢餓的狀態,這算是我蠻欣賞的勇氣,用實際的行動來驗證自己過去的研究,雖然還有許多證據需要累積,但這算是讓人可以嘗試的一個路徑,研究本身除了滿足好奇心外,要是能應用到生活,是多棒的事情呀!當然,談論各種另類飲食療法的人相當多,但要能發表各種嚴謹研究來支持的人卻是少數。
I prefer to see outstanding MDs go into the clinic and train to do research there.
…generating an effective bedside to bench approach is going to require major adjustments in medical education. We will need to introduce more basic science into the medical school curriculum
Celine Lefebvre, G. R., Andrea Califano. (2012). Reverse-engineering human regulatory networks. Wiley Interdiscip Rev Syst Biol Med. doi:10.1002/wsbm.1159
機器學習的重點在於用演算法是基於資料或是案例,而非寫好的規則(rule-based),在這前提下,其實機器學習是個包含很廣的,裡頭很多方法都是從統計學而來的,只是加上資訊工程。(推薦這本Computer Age Statistical Inference,裡頭有蠻多統計學家對於這些事物的看法。)
There is no bright line between machine-learning models and traditional statistical models. However, sophisticated new machine-learning models are well suited to learn from the complex and heterogeneous kinds of data that are generated from modern clinical care, such as medical notes entered by physicians, medical images, continuous monitoring data from sensors, and genomic data to help make medically relevant predictions.
會接觸到這本書,其實是搜尋到台大莊榮輝教授(目前已退休,轉任台科大)的網頁,算是從高中就開始看他準備的網頁資訊(研究生涯),從今日的觀點來看,依舊是非常棒的東西,還好台灣還有這些充滿熱情的教師,在努力散布學習的熱忱,話說回來,這本書是英國劍橋大學 病理學教授William Ian Beardmore Beveridge的書,寫於1950年,時至今日,依舊能帶給人許多的啟發,某些共通性的事物,總是不變的。
The lame in the path outstrip the swift who wander from it
簡單來說,大量的閱讀,不必然代表能給予你做出新研究的能力,因為你閱讀的資料可能提供錯誤的想法,所以為了避免這個結果,大量閱讀必須放在擁有批判性思考的前提下,才對你的智識成長有幫助,否則反而會侷限住你對於問題的想法,在當時後的時代背景,閱讀完所有期刊論文已經是困難挑戰了(哇靠!七十年前就這樣了,那現在不就是整個很崩潰,可見資訊爆炸對於人類算是個古老的問題了),當時候的研究者,會把閱讀所花的時間根據精讀的程度來做分類,這部分也許之後分享約翰霍普金斯統計學家Jeffrey Leek的書How to be a modern scientist時,更近一步分享。
Author, A. A., Author, B. B., & Author, C. C. (Year). Title of article. Title of Periodical, volume number(issue number), pages. https://doi.org/xx.xxx/yyyy
Harvard
經濟學領域
Author-date
Author, A. A., Author, B. B., & Author, C. C. (Year). Title of article. Title of Periodical. Location
MLA
人文科學
Author-page number
Author, A. A., Author, B. B., & Author, C. C. Title of article. Title of Periodical. Year
AMA
生物醫學
Numeric
Author, A. A., Author, B. B., & Author, C. C. Title of article. Title of Periodical. Year. volume(issue):pages
Chicago
人文科學
Notation/Author-date
Author, A. A., Author, B. B., & Author, C. C. (Year) .Title of article. Title of Periodical. volume(issue):pages. doi:xxx.yyy/xxxx.12222.