National Taiwan University

Industrial Technology Research Institute

Jih-Luh Tang

Jeng-Lin Li

Chi-Chun Lee

Yu-Fen Wang

Bor-Sheng Ko

Chien-An Chen

Pei-Shin Jiang

Chien-Ting Lin

Cheng-Tai Chen

Xuan-Hui Lin

Su-Feng Chiu

Wen-Ting Chiang

Chien-ting Lin

This application relates generally to a computer implemented method comprising: receiving a medical record data from a patient, wherein said record comprising a static attribute and a time dependent progression attribute; processing the time dependent progression attributes of medical record data using a trained neural network to into time-series representation, and converting the static attributes into static variables; combining the time-series representation and static variables to multiple vectors; providing a prognosis outcome by a trained classifier using said multiple vectors; wherein the neural network is trained by steps of (a) assembling a training data set comprising a retrospective collection of patients' medical record data wherein said record data comprising collected number of static attributes, time dependent progression attributes and patients' mortality and relapse outcomes; (b) processing the time dependent progression attributes of the training data set using a neural network to convert the time dependent progression attributes into time-series representation; (c) processing the static attributes of the training data set into static variables; and (d) combining the time-series representation and static variables to train a classifier based on the combined time-series representation and static variables.

Systems and methods for prognosis prediction of acute myeloid leukemia patients

A method for in vitro activation and/or expansion of immune cells is provided, including the steps of: a) providing magnetic particles having multi-protrusive surface modified with at least one type of immuno-inducing substance, in which each magnetic particle includes a copolymer core, a polymer layer, a magnetic substance layer, and a silicon-based layer from the inside to the outside; b) providing a cell solution including at least one type of immune cell in the cell solution; and c) bringing the magnetic particles in contact with the cell solution, in which the at least one type of immuno-inducing substance on the surface of the magnetic particle activates and/or expands the at least one type of immune cell in the cell solution.

Method for in vitro activation and/or expansion of immune cells

This application relates generally to automated systems and associated methods for identifying hematological abnormalities. An automated system can include at least one processor that, in operation, is configured to: receive, from a flow cytometer, a flow cytometry data matrix characterizing a tube that is associated with a sample; convert the flow cytometry data matrix into a high dimensional vector; produce a single sample high dimensional vector including a concatenation of multiple high dimensional vectors associated with the sample, wherein the multiple high dimensional vectors comprise the tube high dimensional vector; assemble a training data set including multiple sample high dimensional vectors; receive, from a datastore, outcome information including respective labels associated with each of the multiple sample high dimensional vectors; and train a classifier based on the training data set and the outcome information.

Systems and methods for automated hematological abnormality detection

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Taipei, Taiwan

Jih-Luh Tang